# ratings

draft_name: itu-t-y-3173
overlap_note: Complements Y.3172 architecture; minimal overlap with other documents; evaluation-focused niche
momentum_note: Strong standards momentum; essential companion to Y.3172; industry adoption growing
relevance_note: Highly relevant for measuring autonomous netops maturity and AI system capability assessment
categories: ["Autonomous netops", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:09:58.668841+00:00
summary:
  Proposes evaluation framework and metrics for assessing intelligence levels of AI-enabled future networks. Enables standardized measurement and benchmarking of network intelligence capabilities.

novelty_note:
  Novel contribution in defining intelligence level metrics; extends Y.3172 with measurement framework but uses established evaluation methodologies

maturity_note:
  ITU-T Recommendation with mature evaluation criteria; complements Y.3172 with measurable assessment approach


draft_name: itu-t-y-3174
maturity_note: ITU-T Recommendation status; mature data handling framework aligned with industry best practices
momentum_note: Critical component of ITU-T ML architecture; strong adoption in data-intensive network deployments
relevance_note: Essential for autonomous agent systems requiring reliable data pipelines and governance
categories: ["Data formats/interop", "ML traffic mgmt", "Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:09:58.678592+00:00
summary:
  Establishes framework for data handling, lifecycle management, and preparation supporting machine learning in future networks. Addresses data quality, governance, and ML readiness.

novelty_note:
  Moderately novel data governance approach for ML; applies established data management practices with network-specific ML considerations

overlap_note:
  Complements Y.3172 architecture; some overlap with ETSI ENI-019 on data aspects; largely distinct focus


draft_name: itu-t-y-3176
categories: ["Model serving/inference", "Agent discovery/reg", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:10:09.161656+00:00
summary:
  Defines architecture for integrating machine learning marketplaces into future networks and IMT-2020. Addresses how ML models and services can be discovered, traded, and integrated across network domains.

novelty_note:
  ML marketplace concept for networks is relatively novel, though service marketplaces exist in other domains

maturity_note:
  ITU-T recommendation suggests mature standardization process, but marketplace ecosystems for ML are still emerging

overlap_note:
  Overlaps significantly with Y.3177 (AI-as-a-Service) and Y.3180 (multi-domain ML pipeline) in service integration aspects

momentum_note:
  ITU-T standardization indicates institutional momentum, though ML marketplace adoption in telecom remains limited

relevance_note:
  Relevant for network operators seeking to integrate third-party ML services and monetize ML capabilities


draft_name: itu-t-y-3177
maturity_note: Well-developed recommendation from mature standards body with clear service architecture patterns
categories: ["Model serving/inference", "A2A protocols", "Data formats/interop", "Agent discovery/reg"]
rated_at: 2026-03-08T17:10:09.172435+00:00
summary:
  Establishes architectural framework for AI-as-a-Service to deliver AI capabilities across future networks. Defines service models, interfaces, and integration patterns for AI service provisioning.

novelty_note:
  AI-as-a-Service is a known concept; the novelty lies in ITU-T standardized network-specific framework

overlap_note:
  Heavily overlaps with Y.3176 (marketplace integration), Y.3179 (network automation), and Y.3180 (ML pipeline) in service delivery aspects

momentum_note:
  Strong momentum from ITU-T standardization; AI-as-a-Service is widely adopted in cloud/telecom sectors

relevance_note:
  Highly relevant for operators implementing AI services across networks; foundational for service interoperability


draft_name: itu-t-y-3178
maturity_note: Federated learning is mature; ITU-T recommendation adds maturity through standardized requirements
categories: ["AI safety/alignment", "Data formats/interop", "Policy/governance", "Agent identity/auth"]
rated_at: 2026-03-08T17:10:09.182861+00:00
summary:
  Defines requirements and architectural framework for federated machine learning in distributed network environments. Addresses privacy-preserving ML training across multiple domains without centralizing data.

novelty_note:
  Federated learning is well-established; ITU-T standardization of network-specific federated ML requirements is more novel

overlap_note:
  Relatively unique focus on federated learning; less overlap with other drafts though complements Y.3180 (multi-domain pipelines)

momentum_note:
  Federated learning has strong momentum due to privacy regulations (GDPR, etc.) and multi-stakeholder networks

relevance_note:
  Highly relevant for telecom networks handling sensitive data across multiple carriers and jurisdictions


draft_name: itu-t-y-3179
maturity_note: Network automation maturity is high; established patterns for AI/ML-driven netops already exist
relevance_note: Critical for operators; autonomous netops is a primary use case for AI in telecommunications
categories: ["Autonomous netops", "ML traffic mgmt", "Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:10:09.191695+00:00
summary:
  Provides architectural framework for using AI and machine learning to automate network operations and management. Addresses autonomous network management, self-healing, and optimization capabilities.

novelty_note:
  AI-based network automation is well-established in the industry; ITU-T standardization adds incremental value

overlap_note:
  Overlaps with Y.3177 (service delivery), Y.3180 (ML pipeline), and general AI architecture principles

momentum_note:
  Very high momentum; network operators actively pursuing AI-driven automation for cost reduction and resilience


draft_name: itu-t-y-3180
maturity_note: Framework maturity is moderate; multi-domain orchestration patterns still evolving in practice
momentum_note: Moderate momentum; multi-domain coordination is emerging need but not yet widely deployed
relevance_note: Relevant for complex network environments with multiple service providers and operational domains
categories: ["Data formats/interop", "Policy/governance", "Model serving/inference", "Agent discovery/reg"]
rated_at: 2026-03-08T17:10:09.199805+00:00
summary:
  Defines framework for orchestrating multi-domain ML pipelines across future networks. Addresses end-to-end ML workflows spanning multiple network domains with different ownership and governance.

novelty_note:
  Multi-domain ML coordination is relatively novel in telecom context; addresses integration complexity

overlap_note:
  Overlaps significantly with Y.3176 (marketplace), Y.3177 (AI-as-a-Service), and Y.3178 (federated learning)


draft_name: itu-t-y-3181
maturity_note: Mature recommendation from established standards body with clear governance and review processes
categories: ["AI safety/alignment", "Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:10:24.035423+00:00
summary:
  Establishes architectural framework for trustworthy AI in networking, addressing safety and reliability of ML-based network systems. Focuses on building confidence in AI-driven networking infrastructure through formal architectural guidelines.

novelty_note:
  Trustworthy AI in networking is well-explored; this provides ITU standardization perspective but limited novel architectural concepts

overlap_note:
  Overlaps significantly with Y.3530/Y.3531 on ML in networks and general AI safety literature; moderate differentiation through trustworthiness lens

momentum_note:
  Strong momentum as ITU-T recommendation with international adoption potential; trustworthy AI is high-priority domain

relevance_note:
  Highly relevant to network operators and AI system designers; addresses critical trust concerns in production systems


draft_name: itu-t-y-3530
categories: ["ML traffic mgmt", "Autonomous netops", "Other AI/agent"]
rated_at: 2026-03-08T17:10:24.046441+00:00
summary:
  Provides overview of ML applications in future cloud and network architectures, surveying ML techniques for network optimization. Foundational survey establishing landscape of ML in networking.

novelty_note:
  Survey-level contribution with limited novel technical insights; overview documents are incremental to existing ML-in-networks literature

maturity_note:
  Standardized overview document from ITU-T indicates mature consensus view; well-structured but not cutting-edge

overlap_note:
  Heavy overlap with Y.3531 (both address ML in cloud/networks); also overlaps with Y.3181 (trustworthy ML) and Y.4907 (AI in specialized domains)

momentum_note:
  Moderate momentum as foundational survey; may serve as reference but lacks specific technical innovation to drive adoption

relevance_note:
  Relevant as educational/reference material for understanding ML scope in networks; less actionable than specialized recommendations


draft_name: itu-t-y-3531
categories: ["Model serving/inference", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:10:24.056601+00:00
summary:
  Defines functional architecture for MLaaS (Machine Learning as a Service) in cloud computing environments. Specifies service components, interfaces, and deployment models for ML services.

novelty_note:
  MLaaS architecture is established concept; ITU standardization adds formal structure but lacks significant novel technical contributions

maturity_note:
  Well-matured recommendation from standards body with clear functional decomposition; stable specification

overlap_note:
  Moderate-to-high overlap with Y.3530 (both cloud ML); also relates to model serving/inference aspects discussed in other standards

momentum_note:
  Strong momentum in cloud AI services domain; ITU-T endorsement increases standardization credibility

relevance_note:
  Highly relevant to cloud providers and enterprises deploying ML services; provides standardized reference architecture


draft_name: itu-t-y-4464
momentum_note: High momentum in IoT and edge AI; autonomous agents gaining traction as IoT coordination solution
categories: ["Autonomous netops", "A2A protocols", "Agent discovery/reg", "Other AI/agent"]
rated_at: 2026-03-08T17:10:24.065987+00:00
summary:
  Establishes framework for IoT networks using autonomous agents for distributed intelligence and coordination. Addresses agent roles, interactions, and area network organization.

novelty_note:
  Autonomous agents in IoT are active research area; framework provides ITU perspective but overlaps with established agent architectures and multi-agent systems literature

maturity_note:
  Moderate maturity as recommendation; autonomous agent standards still evolving with less consensus than traditional networking specs

overlap_note:
  Relatively unique focus on agents in IoT domain; some overlap with A2A protocol concepts and agent discovery/registration in other contexts

relevance_note:
  Highly relevant to IoT deployments seeking distributed intelligence; addresses key IoT scalability and autonomy challenges


draft_name: itu-t-y-4907
maturity_note: Mature domain-specific recommendation with clear stakeholder alignment in transportation industry
categories: ["Autonomous netops", "Agent identity/auth", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:10:24.075068+00:00
summary:
  Specifies reference architecture for intelligent transportation systems (ITS) communication networks leveraging AI. Defines components and interfaces for AI-enabled vehicle and infrastructure coordination.

novelty_note:
  AI in transportation is well-established; ITU provides standardized reference but builds on mature domain-specific architectures

overlap_note:
  Relatively unique ITS-specific focus; minimal overlap with other documents except general ML/AI architectural principles

momentum_note:
  Strong momentum driven by automotive and smart city initiatives; AI in ITS is high-priority across industries

relevance_note:
  Highly relevant to transportation authorities, vehicle manufacturers, and infrastructure operators; addresses critical safety and efficiency requirements


draft_name: itu-t-x-1381
maturity_note: Well-established as ITU-T recommendation with formal governance; mature standardization process
overlap_note: Overlaps with X.1382, X.1384 on security aspects; complementary to governance work in FG-AI4H
momentum_note: ITU-T backing indicates institutional momentum; part of coordinated standards family
relevance_note: Directly relevant to telecom operators and vendors managing AI deployment risks
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:34.158496+00:00
summary:
  Framework for assessing AI risks in telecommunication networks. Establishes methodology for identifying and evaluating security and operational threats from AI systems in telecom infrastructure.

novelty_note:
  Risk assessment frameworks for telecom AI are emerging but this provides ITU standardization perspective; moderate novelty in telecom-specific context


draft_name: itu-t-x-1382
maturity_note: Formal ITU-T recommendation status indicates mature standards development process
momentum_note: Part of coordinated ITU-T X.138x family with clear institutional backing
relevance_note: High relevance for telecom service providers implementing AI security controls
categories: ["Policy/governance", "AI safety/alignment", "Agent identity/auth"]
rated_at: 2026-03-08T17:10:34.169194+00:00
summary:
  Specifies security requirements for AI-based solutions deployed in telecommunication networks. Defines controls and safeguards for securing AI systems in telecom environments.

novelty_note:
  Security requirements for telecom AI are emerging area; ITU standardization adds formality but concepts are known

overlap_note:
  Heavy overlap with X.1381 (risk framework) and X.1384 (threats/treatment); complementary rather than distinct


draft_name: itu-t-x-1383
maturity_note: Formal ITU-T recommendation status; mature standardization approach
momentum_note: Strong institutional momentum through ITU-T; part of coordinated standards initiative
relevance_note: Relevant for telecom operators evaluating AI vendor solutions and service quality assurance
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:34.177706+00:00
summary:
  Establishes assessment criteria for evaluating trustworthiness of AI-based telecom services. Provides metrics and evaluation methods for AI system reliability and dependability.

novelty_note:
  Trustworthiness assessment criteria are well-explored in AI literature; application to telecom is incremental

overlap_note:
  Complementary to X.1381-X.1382 but distinct focus on assessment rather than requirements; overlaps with FG-AI4H ethics work


draft_name: itu-t-x-1384
novelty_note: Threat catalogs for AI systems exist broadly; telecom-specific instantiation has moderate novelty
maturity_note: ITU-T recommendation format ensures formal development and review
momentum_note: Part of coordinated ITU-T standards suite with clear institutional support
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:34.185894+00:00
summary:
  Catalogs security threats and risk mitigation measures specific to AI-based telecommunication systems. Identifies threat models and treatment strategies for securing AI in telecom.

overlap_note:
  Significant overlap with X.1381 (risk assessment) and X.1382 (security requirements); forms cohesive standards family

relevance_note:
  Highly relevant for threat modeling, security architecture, and incident response planning in telecom AI systems


draft_name: itu-t-fg-ai4h-del01
momentum_note: Active FG working group indicates ongoing momentum; newer than established ITU-T recommendations
relevance_note: Relevant for healthcare organizations and AI health platforms; lower relevance to telecom operators
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:34.194372+00:00
summary:
  Addresses ethics and governance frameworks for AI applications in healthcare. Establishes principles and governance structures for responsible AI deployment in health services.

novelty_note:
  AI ethics and governance are well-established domains; health-specific focus provides sector context but concepts are known

maturity_note:
  FG working group deliverable indicates active development; less mature than finalized recommendations

overlap_note:
  Unique to healthcare sector; limited overlap with telecom-focused X.138x series except governance principles


draft_name: itu-t-fg-ai4h-del02
novelty_note: Healthcare-specific focus adds domain relevance but data handling principles are generalizable
maturity_note: ITU-T formal recommendation indicates mature standardization process
momentum_note: Part of established ITU-T FG-AI4H series but limited visibility in broader AI standards ecosystem
relevance_note: High relevance for healthcare AI deployments; moderate relevance for general AI systems
categories: ["Policy/governance", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:10:43.494705+00:00
summary:
  ITU-T recommendation addressing data handling practices for AI applications in healthcare. Focuses on data management, quality, and governance specific to health AI systems.

overlap_note:
  Significant overlap with ISO/IEC 22989 (terminology) and ISO/IEC 42001 (management systems) on data governance aspects


draft_name: itu-t-fg-ai4h-del7-2
novelty_note: Clinical validation framework is domain-specific; evaluation approaches have broader applicability
maturity_note: ITU-T formal recommendation with structured evaluation criteria indicates maturity
overlap_note: Moderate overlap with ISO/IEC 23894 (risk management) on assessment and evaluation components
momentum_note: Specialized healthcare focus limits cross-domain adoption momentum
relevance_note: Critical for healthcare AI; limited relevance outside medical domain
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:10:43.505253+00:00
summary:
  ITU-T recommendation on clinical evaluation methodologies for AI in healthcare. Establishes assessment criteria and validation approaches for health AI systems.


draft_name: iso-iec-42001-2023
maturity_note: Formal ISO/IEC standard released in 2023 indicates high maturity and international consensus
momentum_note: Strong momentum as foundational AI governance standard with broad organizational adoption potential
relevance_note: Highly relevant across all AI deployment contexts and organizational sizes
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:43.515626+00:00
summary:
  ISO/IEC standard establishing comprehensive AI management system requirements covering governance, risk, and operational controls. Applies across organizational AI implementations.

novelty_note:
  Systematic management framework approach is novel for AI; adapts established management system patterns to AI context

overlap_note:
  Complements rather than heavily overlaps; provides overarching framework that encompasses other standards


draft_name: iso-iec-22989-2022
novelty_note: Comprehensive terminology standardization addresses fragmentation in AI nomenclature
maturity_note: Published ISO/IEC standard from 2022; represents mature consensus on AI conceptual framework
momentum_note: Strong adoption momentum as fundamental reference for AI standards ecosystem
relevance_note: Essential foundation for all AI-related work; critical for interoperability and communication
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:10:43.525134+00:00
summary:
  ISO/IEC standard defining core AI concepts and establishing standardized terminology across the field. Foundational reference for AI concept consistency.

overlap_note:
  Minimal overlap; provides foundational definitions supporting other standards rather than duplicating content


draft_name: iso-iec-23894-2023
maturity_note: Formal ISO/IEC standard released in 2023 with established risk management methodology
momentum_note: High momentum as critical component of AI safety and governance frameworks
relevance_note: Highly relevant for responsible AI deployment across all organizational and domain contexts
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:10:43.534680+00:00
summary:
  ISO/IEC guidance standard for managing risks in AI system development and deployment. Addresses identification, analysis, and mitigation of AI-specific risks.

novelty_note:
  AI-specific risk management guidance extends traditional risk frameworks to AI domain characteristics

overlap_note:
  Moderate overlap with ISO/IEC 42001 on risk governance; provides specialized depth on risk management aspects


draft_name: iso-iec-23053-2022
overlap_note: Moderate overlap with 5338 and 5339 which build upon this framework; more generic than specialized
momentum_note: Published 2022; foundational but not driving significant recent innovation in the field
categories: ["Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:10:53.081541+00:00
summary:
  Establishes a generic framework for AI systems built on ML technology, defining the fundamental architecture and components. Serves as a foundational reference for understanding ML-based AI system structure.

novelty_note:
  Early foundational framework; describes generic ML system architecture without specialized focus on novel domains

maturity_note:
  Well-established ISO standard from 2022 with broad industry acceptance; mature and stable specification

relevance_note:
  Highly relevant as baseline reference for understanding ML-based AI system structures across domains


draft_name: iso-iec-38507-2022
novelty_note: Governance guidance is relatively well-established domain; limited novelty in approach
maturity_note: Mature 2022 standard addressing established governance concerns with proven methodologies
momentum_note: 2022 publication; governance focus is steady but not accelerating in innovation
relevance_note: Highly relevant for organizational decision-makers evaluating AI risk and compliance implications
categories: ["Policy/governance"]
rated_at: 2026-03-08T17:10:53.091614+00:00
summary:
  Provides organizational governance guidance for AI deployment, focusing on board and executive decision-making implications. Addresses strategic and risk management dimensions of AI adoption.

overlap_note:
  Minimal overlap with technical standards; focuses on organizational governance rather than system architecture or processes


draft_name: iso-iec-5338-2023
maturity_note: Recent 2023 standard; incorporates evolving AI development practices with good maturity level
overlap_note: Significant overlap with 23053 (architecture) and 5339 (application guidance); builds on both
momentum_note: 2023 publication shows continued standardization momentum in AI lifecycle management
relevance_note: Highly relevant for practitioners managing AI system development and operational processes
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:10:53.101681+00:00
summary:
  Defines standardized processes and activities for the complete AI system lifecycle from development through operation. Provides process-level guidance complementing architectural frameworks.

novelty_note:
  Lifecycle process standards are established practice; adapts software engineering methodologies to AI domain


draft_name: iso-iec-5339-2024
maturity_note: 2024 publication suggests active development; maturity depends on adoption and practical validation
overlap_note: High overlap with 5338 (processes), 23053 (framework), and 38507 (governance considerations)
momentum_note: 2024 release indicates strong momentum in practical AI application standardization
relevance_note: Highly relevant for organizations implementing AI, combining assessment and risk evaluation
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:10:53.110545+00:00
summary:
  Provides practical guidance for applying AI within organizational contexts, including use case analysis and risk assessment frameworks. Bridges gap between frameworks and implementation.

novelty_note:
  Application guidance frameworks are evolving; use case analysis and risk assessment methodologies are maturing but not novel


draft_name: iso-iec-42005-2025
momentum_note: Latest 2025 standard indicates strong current momentum in impact assessment as emerging priority
relevance_note: Increasingly relevant as stakeholders demand broader impact visibility beyond technical measures
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:10:53.120032+00:00
summary:
  Provides guidance for systematically assessing both positive and negative impacts of AI systems on organizations and stakeholders. Addresses impact evaluation methodology.

novelty_note:
  Impact assessment methodology for AI is emerging domain; represents newer focus on holistic impact beyond technical safety

maturity_note:
  2025 publication suggests early maturity; methodology likely still evolving with limited field validation

overlap_note:
  Moderate overlap with 5339 (risk assessment) and 38507 (governance risks); adds broader impact scope


draft_name: iso-iec-tr-24028-2020
momentum_note: Older (2020) foundational work; superseded by more specific technical standards in 2024
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:11:04.478309+00:00
summary:
  Foundational overview of trustworthiness in AI systems, covering key risks, challenges, and mitigation approaches. Establishes conceptual framework for understanding AI reliability and safety across domains.

novelty_note:
  Early landscape overview with limited technical depth; provides broad framing rather than novel methodologies

maturity_note:
  Technical report format indicates exploratory/informational status; predates more recent standardization work

overlap_note:
  Overlaps significantly with governance and safety themes in later standards, particularly TS 6254 and 12792

relevance_note:
  Relevant for establishing trustworthiness principles but lacks specific technical guidance for implementation


draft_name: iso-iec-tr-24029-1-2021
relevance_note: Highly relevant for ML model evaluation and safety validation in AI systems
categories: ["AI safety/alignment", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:11:04.488406+00:00
summary:
  Technical overview of neural network robustness properties and assessment methodologies. Focuses on evaluation approaches for understanding model behavior under adversarial and distributional challenges.

novelty_note:
  Part 1 of multi-part series on robustness; provides background rather than novel assessment techniques

maturity_note:
  Technical report status and 2021 date suggest early-stage guidance; likely superseded by more mature standards

overlap_note:
  Robustness relates to trustworthiness (24028) and explainability (TS 6254) but addresses distinct technical dimension

momentum_note:
  Limited momentum; no subsequent updates or related standards appear to build on this Part 1 framework


draft_name: iso-iec-tr-24030-2021
maturity_note: Technical report with wide scope; useful reference but lacks prescriptive or normative guidance
categories: ["Other AI/agent", "Policy/governance"]
rated_at: 2026-03-08T17:11:04.497510+00:00
summary:
  Compendium of representative AI use cases across multiple domains and application areas. Serves as reference for understanding practical AI deployment patterns and requirements.

novelty_note:
  Use case collection provides domain grounding but limited analytical novelty; primarily organizational/reference material

overlap_note:
  Unique positioning as use case reference; supports but doesn't overlap directly with robustness, explainability, or transparency standards

momentum_note:
  2021 publication with no apparent follow-up updates; static reference material rather than evolving guidance

relevance_note:
  Useful context for understanding AI system diversity but limited direct relevance to technical implementation standards


draft_name: iso-iec-ts-6254-2024
momentum_note: 2024 publication indicates active standardization momentum in explainability/interpretability space
relevance_note: Highly relevant for responsible AI deployment, regulatory compliance (EU AI Act), and user trust
categories: ["AI safety/alignment", "Policy/governance", "Human-agent interaction", "Other AI/agent"]
rated_at: 2026-03-08T17:11:04.506978+00:00
summary:
  Defines objectives and systematic approaches for achieving explainability in ML models and AI systems. Provides frameworks for making AI decisions interpretable and understandable to users.

novelty_note:
  Recent (2024) work addressing critical explainability gap; likely incorporates newer research on interpretability methods

maturity_note:
  Technical specification format with current publication date indicates mature, implementation-ready guidance

overlap_note:
  Explainability overlaps with transparency (12792) and trustworthiness (24028) concepts; complementary rather than redundant


draft_name: iso-iec-12792-2024
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:11:04.516203+00:00
summary:
  Establishes comprehensive taxonomy for AI system transparency, enabling structured classification and governance of disclosure practices. Supports organizational understanding and stakeholder communication about AI behavior.

novelty_note:
  Novel taxonomy approach to transparency; 2024 timing suggests incorporation of recent transparency/governance developments

maturity_note:
  Full standard (not technical report) with recent publication indicates mature, normative framework ready for adoption

overlap_note:
  Transparency taxonomy complements explainability (TS 6254) and trustworthiness (24028); distinct but related perspectives

momentum_note:
  2024 publication in active governance/transparency standardization wave; aligns with regulatory momentum

relevance_note:
  Critical for regulatory compliance, stakeholder governance, and responsible AI frameworks; directly addresses transparency requirements


draft_name: iso-iec-2382-28-1995
maturity_note: Mature standard from 1995, well-established as reference material for AI terminology
momentum_note: Foundational reference work with limited active development momentum beyond periodic updates
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:11:14.174841+00:00
summary:
  ISO/IEC standard defining basic vocabulary and concepts for artificial intelligence and expert systems. Provides foundational terminology for AI and knowledge-based systems in information technology contexts.

novelty_note:
  Primarily definitional/standardization work; limited novel technical contributions beyond vocabulary codification

overlap_note:
  Overlaps with general AI/agent concepts but provides baseline vocabulary across multiple related standards

relevance_note:
  Limited relevance to modern agent protocols and distributed systems; focuses on historical AI/expert system terminology


draft_name: iso-iec-2382-29-1999
novelty_note: Standard vocabulary reference with limited technical innovation; primarily terminological alignment
maturity_note: Established 1999 standard, mature and stable with accepted terminology
overlap_note: Speech-specific subset of broader AI vocabulary; some overlap with human-agent interaction domain
momentum_note: Legacy standard with limited momentum for advancement in modern speech AI era
relevance_note: Moderate relevance to human-agent interaction but outdated relative to modern NLP/speech systems
categories: ["Data formats/interop", "Human-agent interaction"]
rated_at: 2026-03-08T17:11:14.185961+00:00
summary:
  ISO/IEC vocabulary standard for AI speech recognition and synthesis terminology. Establishes standardized definitions and concepts for speech-based AI systems.


draft_name: iso-iec-2382-31-1997
novelty_note: Definitional standard; codifies existing ML terminology without advancing novel technical concepts
maturity_note: Established 1997 standard with stable, widely-referenced definitions
overlap_note: Foundational ML vocabulary with potential overlap to model serving and autonomous systems domains
momentum_note: Limited active development; serves as reference baseline rather than innovation driver
relevance_note: Moderate relevance as foundational vocabulary for ML-based agents and autonomous systems
categories: ["Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:11:14.194931+00:00
summary:
  ISO/IEC standard establishing vocabulary for machine learning terminology and concepts. Defines core ML concepts within the information technology vocabulary framework.


draft_name: iso-iec-2382-34-1999
novelty_note: Terminology standardization work; provides vocabulary codification rather than technical innovation
maturity_note: 1999 standard; moderately mature but increasingly dated relative to modern deep learning advances
overlap_note: Neural network vocabulary with overlap to model serving and AI safety considerations
momentum_note: Minimal momentum; lacks engagement with modern deep learning and transformer-based systems
categories: ["Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:11:14.204479+00:00
summary:
  ISO/IEC vocabulary standard for neural network terminology and concepts in AI. Establishes standardized definitions for neural network systems and related AI applications.

relevance_note:
  Limited relevance to contemporary agent protocols; vocabulary outdated for modern neural architectures


draft_name: iso-tr-15801-2004
maturity_note: Established 2004 technical report with mature guidance on information management practices
momentum_note: Legacy technical report with limited momentum in modern distributed agent systems
categories: ["Data formats/interop", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:11:14.213845+00:00
summary:
  ISO technical report addressing trustworthiness, reliability, authenticity and integrity of electronically stored information across full document lifecycle. Applicable to imaging, workflow, and archival systems.

novelty_note:
  Practical technical guidance on trust and integrity in electronic information systems; somewhat novel approach to lifecycle management

overlap_note:
  Minimal overlap with AI/agent protocol standards; focuses on document/data integrity rather than agent communication

relevance_note:
  Low direct relevance to agent protocols; potentially applicable to trusted data provenance in agent systems


draft_name: iso-np-20319
momentum_note: No publication date; minimal evidence of active development or stakeholder momentum in abstracts.
categories: ["Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:11:26.383305+00:00
summary:
  Specifies profiles for Ethernet-based control networks supporting real-time communication and autonomous decentralized systems. Addresses industrial networking standards for distributed control architectures.

novelty_note:
  Incremental standardization of existing Ethernet control concepts; limited novel architectural contributions.

maturity_note:
  Early-stage ISO new proposal (NP) status; standard development incomplete with no publication date established.

overlap_note:
  Moderate overlap with existing industrial Ethernet standards (PROFINET, EtherCAT); fills specific niche for autonomous decentralized control.

relevance_note:
  Relevant for industrial automation but limited applicability to AI/autonomous agent systems beyond legacy control networks.


draft_name: iso-24801-2-2007
momentum_note: Established standard from 2007; no indication of new momentum or updates in the abstract.
categories: ["Human-agent interaction"]
rated_at: 2026-03-08T17:11:26.394322+00:00
summary:
  Establishes competency requirements and training standards for recreational scuba divers achieving Level 2 (Autonomous diver) certification. Specifies assessment criteria and conditions for training delivery.

novelty_note:
  Minimal relevance to technical standards; domain-specific human certification in recreational diving with no AI/agent systems involvement.

maturity_note:
  Published standard (2007) with established certification framework and clear implementation pathways.

overlap_note:
  Completely distinct domain; heavy overlap only with other recreational diving certification standards (ISO 24800 series).

relevance_note:
  Not relevant to AI, autonomous systems, or agent-based technologies; purely human recreational skill certification.


draft_name: iso-iec-42006-2025
momentum_note: Published July 2025; represents active standardization momentum in AI governance and certification.
categories: ["AI safety/alignment", "Policy/governance", "Agent identity/auth"]
rated_at: 2026-03-08T17:11:26.404573+00:00
summary:
  Specifies auditing and certification requirements for bodies assessing AI management systems (AIMS) per ISO/IEC 42001. Establishes conformity assessment procedures and competency criteria for third-party certification bodies.

novelty_note:
  Novel as formalized certification standard for AI management systems; extends ISO/IEC 17021-1 into emerging AI governance domain.

maturity_note:
  Recent publication (2025) with clear normative references and implementation framework based on established conformity assessment standards.

overlap_note:
  Builds on established ISO/IEC 17021-1 framework but novel application to AI systems; limited overlap with existing AI standards.

relevance_note:
  Highly relevant to AI safety, governance, and institutional trust frameworks; addresses emerging regulatory demands for AI system accountability.


draft_name: iso-22373-2025
categories: ["Data formats/interop", "Policy/governance", "Agent identity/auth"]
rated_at: 2026-03-08T17:11:26.413559+00:00
summary:
  Provides framework for establishing trustworthy supply and value chains through authenticity, integrity, and trust verification of products and documents. Includes interoperable data structures for stakeholder information exchange.

novelty_note:
  Novel integration of supply chain trust with generic interoperability requirements; applicable beyond traditional product authentication.

maturity_note:
  Recently published (November 2025) with defined framework, data structure specifications, and stakeholder guidelines.

overlap_note:
  Overlaps with product authentication and supply chain standards but novel in establishing generic trust framework across all product types.

momentum_note:
  Very recent publication (2025) indicates active standardization and organizational focus on supply chain trustworthiness.

relevance_note:
  Relevant for distributed autonomous systems requiring inter-agent trust verification and supply chain authentication; applicable to AI system provenance.


draft_name: iso-tr-15801-2009
momentum_note: Published 2009; no evidence of updates or renewed momentum in recent years.
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:11:26.422710+00:00
summary:
  Provides recommendations for implementing trustworthy and reliable document management systems storing electronic information. Addresses policies, procedures, technology, and audit requirements ensuring information integrity over time.

novelty_note:
  Incremental guidance on document management reliability; standard approach to long-term information preservation without novel methodologies.

maturity_note:
  Published technical report (2009) with established implementation frameworks; stable but aging standard.

overlap_note:
  Significant overlap with ISO 14721 (OAIS) and other digital preservation standards; addresses similar trustworthiness concerns.

relevance_note:
  Limited relevance to autonomous agents; tangentially relevant for agent audit logging and trustworthiness documentation.


draft_name: iso-39003-2023
maturity_note: Published standard with defined scope, but lacks enforcement mechanisms and technical precision
overlap_note: Unique focus on ethical guidance; some overlap with broader AV safety standards
relevance_note: Relevant for AV safety governance but limited direct technical applicability
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:11:37.647536+00:00
summary:
  Provides guidance on ethical considerations for level 5 autonomous vehicles regarding road traffic safety decision-making. Outlines protocol guidelines for designers/manufacturers to self-certify ethical aspects without prescribing specific technical controls or outcomes.

novelty_note:
  Addresses emerging ethical framework needs for fully autonomous vehicles, though ethical guidance for AVs is becoming more common

momentum_note:
  Published but represents early-stage ethical guidance; limited evidence of industry adoption or integration


draft_name: iso-ts-12813-2009
maturity_note: Published technical specification with clear scope and mature data definitions
momentum_note: Published 2009; part of legacy toll system architecture, limited recent activity
relevance_note: Narrow applicability to toll collection domain; limited relevance to broader autonomous systems
categories: ["Data formats/interop", "Agent identity/auth", "A2A protocols"]
rated_at: 2026-03-08T17:11:37.657813+00:00
summary:
  Defines short-range communication requirements for compliance checking between vehicle on-board equipment and roadside interrogators in autonomous electronic toll collection systems. Specifies data syntax and semantics for verifying toll payment compliance.

novelty_note:
  Incremental extension of toll collection standards; compliance checking protocols are well-established

overlap_note:
  Heavy overlap with ISO 17573 and related EFC standards; part of established toll collection ecosystem


draft_name: iso-ts-17575-1-2010
maturity_note: Published technical specification with comprehensive data definitions and clear scope
overlap_note: Part of integrated ISO/TS 17575 suite; heavy overlap with Parts 2 and 3; extends ISO 12813
momentum_note: Published 2010; foundational for EFC systems but limited evidence of recent evolution
relevance_note: Domain-specific to electronic fee collection; limited applicability beyond toll systems
categories: ["Data formats/interop", "A2A protocols"]
rated_at: 2026-03-08T17:11:37.668363+00:00
summary:
  Defines data exchange format and semantics between vehicle on-board equipment and backend systems in autonomous toll collection. Specifies reporting, contract, road usage, account, and compliance checking data elements for charge report generation.

novelty_note:
  Standard data format definition for toll systems; similar specifications exist across EFC implementations


draft_name: iso-ts-17575-2-2010
maturity_note: Published technical specification with abstract and concrete API definitions
overlap_note: Integral component of ISO/TS 17575 suite; directly implements Part 1 specifications
momentum_note: Published 2010; limited recent activity or updates to communication standards
relevance_note: Technical specification for toll collection communication; narrow domain applicability
categories: ["Data formats/interop", "A2A protocols"]
rated_at: 2026-03-08T17:11:37.679155+00:00
summary:
  Specifies abstract API definition for conveying ISO/TS 17575-1 data elements over various communication stacks and media, focusing on mobile communication links. Defines semantic specifications with concrete API examples provided in annexes.

novelty_note:
  Communication API specification for toll systems; generic communication patterns are well-established


draft_name: iso-ts-17575-3-2011
novelty_note: Toll system configuration data standard; incremental component of established EFC architecture
maturity_note: Published technical specification with defined context data requirements
overlap_note: Complete integration with ISO/TS 17575-1 and 17575-2; forms unified EFC specification suite
momentum_note: Published 2011; part of stable toll collection standards with minimal recent evolution
relevance_note: Specialized data format for toll system configuration; limited relevance outside EFC
categories: ["Data formats/interop", "A2A protocols"]
rated_at: 2026-03-08T17:11:37.689137+00:00
summary:
  Defines context data for autonomous electronic fee collection systems, specifying geographical objects and charging/reporting rules. Transfers system configuration data to vehicle on-board equipment to direct data collection and reporting behavior.


draft_name: iso-ts-17575-4-2011
novelty_note: Specific to toll collection domain with moderate technical novelty in multi-regime coordination
maturity_note: Published ISO/TS standard from 2011 with established maturity
overlap_note: Minimal overlap with IoT/autonomous systems drafts; domain-specific to transportation
momentum_note: Older standard with limited recent activity signals
relevance_note: Relevant primarily to electronic toll collection systems, limited broader applicability
categories: ["A2A protocols", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:11:46.862879+00:00
summary:
  Defines information exchange protocols for electronic fee collection systems operating multiple overlapping toll regimes. Specifies functional details and data elements for autonomous on-board equipment to interact with backend systems while handling complex charge rule coordination.


draft_name: iso-iec-30147-2021
novelty_note: Moderate novelty in formalizing trustworthiness assessment methodologies for IoT
maturity_note: Published ISO/IEC standard from 2021, recent and established
overlap_note: Overlaps with ISO/IEC TS 30149 on trustworthiness principles; related to IoT architecture standards
momentum_note: Recent publication suggests active standards development in IoT trustworthiness
relevance_note: Relevant to autonomous systems trust frameworks and agent reliability assessment
categories: ["AI safety/alignment", "Agent identity/auth", "Policy/governance"]
rated_at: 2026-03-08T17:11:46.874506+00:00
summary:
  Establishes methodology framework for assessing trustworthiness of IoT systems and services. Provides standardized approach to evaluating system reliability, security, and dependability in IoT contexts.


draft_name: iso-iec-ts-30149-2024
novelty_note: Low novelty as principled framework document building on existing architecture reference
maturity_note: Very recent 2024 standard indicating active standardization momentum
overlap_note: Heavy overlap with ISO/IEC 30147 on trustworthiness; both build on 30141 reference architecture
momentum_note: Latest publication in active IoT trustworthiness standards development track
relevance_note: Highly relevant to autonomous agent design and trustworthy IoT system governance
categories: ["AI safety/alignment", "Agent identity/auth", "Policy/governance"]
rated_at: 2026-03-08T17:11:46.884730+00:00
summary:
  Provides foundational principles for IoT trustworthiness aligned with ISO/IEC 30141 reference architecture. Establishes conceptual framework for implementing trustworthy IoT systems and services.


draft_name: iso-iec-30184-2024
novelty_note: Moderate novelty in connected home IoT identification architecture and requirements
maturity_note: Very recent 2024 standard indicating mature IoT standardization ecosystem
overlap_note: Moderate overlap with other ISO/IEC 30000-series IoT standards on identity and architecture
momentum_note: Latest standards activity shows strong momentum in IoT autonomous systems
relevance_note: Relevant to agent identity/authentication and autonomous system discovery in IoT contexts
categories: ["Agent identity/auth", "Agent discovery/reg", "Data formats/interop", "Autonomous netops"]
rated_at: 2026-03-08T17:11:46.894807+00:00
summary:
  Specifies requirements, architecture, and operational procedures for autonomous identification of IoT objects in connected home environments. Defines functional entities, interfaces, and operation procedures while excluding data format and identifier assignment details.


draft_name: iso-ts-13141-2010
novelty_note: Moderate novelty in specialized short-range communication for EFC localization augmentation
maturity_note: Published ISO/TS standard from 2010 with established maturity despite age
overlap_note: Unique to toll collection domain; minimal overlap with other drafts
momentum_note: Older standard with limited signals of recent activity or updates
relevance_note: Highly specialized to electronic toll collection; limited broader autonomous systems relevance
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:11:46.903463+00:00
summary:
  Establishes short-range communication requirements for location augmentation in autonomous electronic fee collection systems. Specifies security mechanisms protecting on-board equipment from false road-side equipment and defines Application Data Unit attributes for localization services.


draft_name: iso-awi-29999
momentum_note: Limited momentum indicators; no publication date suggesting early-stage development
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:11:57.264689+00:00
summary:
  Proposes ethical guidelines for applying AI technology in education and learning services across all organization types. Addresses general principles, integrated frameworks, and essential actions for responsible AI deployment in educational contexts.

novelty_note:
  Ethics in education-specific AI is somewhat novel, though general AI ethics standards exist; educational focus is distinctive

maturity_note:
  Appears to be in early stages (AWI status); abstract lacks implementation details and concrete mechanisms

overlap_note:
  Overlaps with general AI ethics frameworks but education-specific application differentiates it from broader standards

relevance_note:
  Relevant to education sector stakeholders but narrower applicability than cross-sector AI governance standards


draft_name: iso-16363-2012
maturity_note: Published in 2012; mature, widely-adopted standard with established assessment methodologies
momentum_note: Mature standard with established use cases; not cutting-edge but stable reference for digital trust
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:11:57.275446+00:00
summary:
  Defines recommended practices for assessing trustworthiness of digital repositories across all types. Provides certification basis for evaluating repository integrity and reliability.

novelty_note:
  Established standard for repository certification; not AI-specific but foundational for digital trust infrastructure

overlap_note:
  Minimal overlap with AI-specific standards; addresses general digital repository trust rather than AI systems

relevance_note:
  Relevant primarily to digital preservation and data management; limited direct relevance to AI governance


draft_name: iso-iec-dis-27090
maturity_note: DIS (Draft International Standard) status indicates early development phase; not yet finalized
momentum_note: Strong momentum in AI security standardization; timely response to emerging AI deployment risks
categories: ["AI safety/alignment", "Policy/governance", "Agent identity/auth"]
rated_at: 2026-03-08T17:11:57.295948+00:00
summary:
  Addresses security threats and compromises specific to AI systems throughout their lifecycle. Provides organizations guidance on understanding consequences and detection/mitigation strategies for AI-specific security risks.

novelty_note:
  Novel focus on AI-specific security threats distinct from general cybersecurity; emerging area with growing importance

overlap_note:
  Moderate overlap with general cybersecurity standards (ISO 27000 series) but AI-threat specificity is differentiated

relevance_note:
  High relevance to organizations deploying AI systems; addresses critical security gap in AI governance


draft_name: iso-iec-dis-27091
maturity_note: DIS status indicates early development; complementary to ISO 27090 but not yet finalized
categories: ["AI safety/alignment", "Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:11:57.305608+00:00
summary:
  Provides guidance for organizations to address privacy risks in AI systems and machine learning models across their lifecycle. Establishes mechanisms for identifying, evaluating, and treating privacy-specific risks.

novelty_note:
  Novel focus on privacy risks in ML/AI systems; distinct from general privacy standards and addresses lifecycle concerns

overlap_note:
  Moderate overlap with ISO 27001/27002 privacy frameworks but AI/ML-specific application adds differentiation

momentum_note:
  Strong momentum reflecting urgent need for AI privacy guidance; addresses regulatory and ethical imperatives

relevance_note:
  High relevance given privacy concerns in AI/ML deployment; critical for GDPR and emerging AI regulations


draft_name: iso-16919-2014
maturity_note: Published 2014; mature supporting standard with established audit certification frameworks
momentum_note: Stable mature standard; limited momentum as supporting infrastructure document
relevance_note: Minimal relevance to AI governance; focuses on digital repository audit procedures only
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:11:57.334458+00:00
summary:
  Specifies requirements for bodies providing audit and certification of digital repositories using ISO 16363 standards. Defines qualifications, assessment processes, and accreditation support for certification organizations.

novelty_note:
  Not novel; establishes operational/procedural standards for existing ISO 16363 certification infrastructure

overlap_note:
  Heavy overlap with ISO 16363; companion standard for implementing and certifying against that framework


draft_name: iso-24801-2-2014
maturity_note: Mature ISO standard published in 2014 with established implementation practices
overlap_note: Unique focus on recreational diving; no overlap with other autonomous systems standards
momentum_note: Static standard in niche application domain; unlikely to evolve significantly
relevance_note: Not relevant to autonomous agents, AI systems, or network operations
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:12:08.162729+00:00
summary:
  Specifies competencies and evaluation criteria for scuba divers seeking Level 2 (Autonomous diver) qualification. Defines training conditions and requirements aligned with recreational diving service standards.

novelty_note:
  Domain-specific certification standard with limited relevance to autonomous systems in technical/digital contexts


draft_name: iso-17757-2017
maturity_note: Published 2017 with comprehensive safety framework; industry-specific maturity
overlap_note: Minimal overlap; distinct from autonomous network/agent systems covered in other standards
momentum_note: Specialized industrial standard; moderate evolution potential as autonomous machinery advances
relevance_note: Limited relevance to autonomous agents, network systems, or digital governance
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:12:08.172307+00:00
summary:
  Establishes safety requirements for autonomous and semi-autonomous machines in earth-moving and mining operations. Covers system safety, hardware, software, infrastructure, and lifecycle considerations.

novelty_note:
  Addresses autonomous physical systems but focuses narrowly on industrial machinery safety rather than digital agents or protocols


draft_name: iso-18829-2017
novelty_note: Focuses on document management system evaluation rather than autonomous agents or dynamic systems
maturity_note: Published 2017 as methodology standard building on prior trustworthiness frameworks
overlap_note: Some tangential relevance to data formats/interop and governance but primarily document-centric
momentum_note: Incremental evolution likely as ESI environments and compliance needs evolve
relevance_note: Minimal relevance; tangentially relates to data governance but not autonomous systems
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:12:08.182988+00:00
summary:
  Establishes assessment methodology for evaluating trustworthiness and reliability of electronically stored information in ECM/EDRM systems. Defines compliance evaluation procedures for records management environments.


draft_name: iso-ts-13141-2010-cor-1-2013
novelty_note: Narrow technical correction with limited scope; specialized application domain (toll collection)
maturity_note: Corrigendum to 2010 standard; maintenance-level maturity rather than development
momentum_note: Corrigendum indicates aging standard with limited momentum for new development
relevance_note: Niche relevance to toll/fee collection systems; minimal broader applicability
categories: ["A2A protocols", "Autonomous netops"]
rated_at: 2026-03-08T17:12:08.193803+00:00
summary:
  Technical corrigendum to standard addressing localization augmentation communication for autonomous systems in electronic fee collection context.

overlap_note:
  Related to autonomous systems communication but highly specialized; some overlap with A2A protocols conceptually


draft_name: iso-ts-17575-1-2010-cor-1-2013
maturity_note: 2010 standard with 2013 correction; maintenance-level rather than active development
momentum_note: Aging corrigendum with minimal indication of active development or adoption momentum
relevance_note: Limited relevance; application-specific to electronic fee collection infrastructure
categories: ["Data formats/interop", "A2A protocols", "Autonomous netops"]
rated_at: 2026-03-08T17:12:08.204169+00:00
summary:
  Technical corrigendum to Part 1 of standard defining application interfaces for autonomous systems in electronic fee collection charging systems.

novelty_note:
  Corrigendum to interface definition standard; specialized to toll/charging domain with limited generalization

overlap_note:
  Related to autonomous system interfaces and data formats but highly domain-specific; moderate conceptual overlap with data formats/interop


draft_name: iso-ts-17575-3-2011-cor-1-2013
novelty_note: Corrigendum to existing standard; primarily corrections rather than novel contributions
maturity_note: Formally published ISO technical corrigendum with established committee oversight (ISO/TC 204)
overlap_note: Heavy overlap with iso-17575-3-2016; represents earlier version of same specification
momentum_note: Superseded by 2016 version; represents legacy technical clarification
relevance_note: Relevant for toll systems but limited broader applicability; specific to EFC context data
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:12:19.267240+00:00
summary:
  Technical corrigendum to ISO/TS 17575-3:2011 addressing context data definitions for electronic fee collection in autonomous toll systems. Corrects and clarifies data exchange specifications between Front End and Back End systems.


draft_name: iso-17575-1-2016
maturity_note: Published ISO standard with mature governance structure and committee oversight
overlap_note: Moderate overlap with other ISO 17575 parts; part of coherent standard family
momentum_note: Established standard but specific to narrow EFC domain; limited momentum beyond toll operators
categories: ["Data formats/interop", "A2A protocols", "Agent identity/auth"]
rated_at: 2026-03-08T17:12:19.277019+00:00
summary:
  Defines data exchange formats and semantics for charging between Front End (OBE) and Back End systems in autonomous toll schemes. Specifies charge reports, account management, security, and versioning data elements.

novelty_note:
  Domain-specific standardization of existing toll collection concepts; incremental evolution from prior versions

relevance_note:
  Domain-specific relevance to electronic fee collection; minimal relevance to general autonomous agent systems


draft_name: iso-17575-2-2016
maturity_note: Formally published ISO standard with established technical committee (ISO/TC 204) governance
overlap_note: Integral part of ISO 17575 family; overlaps with other parts in scope and context
momentum_note: Narrow domain focus limits broader adoption; limited evolution momentum
categories: ["A2A protocols", "Data formats/interop"]
rated_at: 2026-03-08T17:12:19.286402+00:00
summary:
  Specifies communication protocols and APIs for conveying ISO 17575 data structures over various communication stacks and media. Defines medium-independent abstract API for Front End and Back End system integration.

novelty_note:
  Standard API abstraction for toll system communication; incremental addition to modular standard suite

relevance_note:
  Relevant for toll system architects; minimal applicability to general autonomous agent communication


draft_name: iso-17575-3-2016
maturity_note: Published ISO standard with formal committee structure and governance
overlap_note: Direct successor to iso-ts-17575-3-2011-cor-1-2013; substantial overlap with earlier version
momentum_note: Stable mature standard; limited ongoing momentum beyond maintenance
relevance_note: Specialized relevance to EFC systems; limited broader applicability to general autonomous systems
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:12:19.295233+00:00
summary:
  Defines content, semantics, and format of context data exchanged between Front End and Back End in autonomous toll systems. Specifies tariff information, charging rules, vehicle liability, and charge report requirements.

novelty_note:
  Mature specification of toll context data structures; iterative refinement from 2011 corrigendum version


draft_name: iso-dis-17575-4
maturity_note: Draft status (DIS) indicates pre-publication; undergoing formal standardization process
overlap_note: Integral extension to ISO 17575 family; inherent overlap with parts 1-3
momentum_note: Draft status suggests active development; roaming is emerging requirement in EFC ecosystem
relevance_note: Specialized relevance to multi-operator toll schemes; narrow domain applicability
categories: ["Data formats/interop", "Agent discovery/reg", "A2A protocols"]
rated_at: 2026-03-08T17:12:19.305238+00:00
summary:
  Draft ISO standard addressing roaming specifications for autonomous electronic fee collection systems. Extends ISO 17575 framework to support cross-border and multi-operator toll scheme interoperability.

novelty_note:
  Adds roaming capability to EFC framework; represents forward extension to established standard family


draft_name: iso-12813-2015
maturity_note: Published ISO standard from 2015; fully mature specification
overlap_note: Minimal overlap; highly specialized to EFC domain with unique compliance-checking requirements
momentum_note: Mature standard with no indication of active development or updates
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:12:29.331150+00:00
summary:
  Defines short-range communication requirements for compliance checking between vehicle on-board equipment and roadside interrogators in autonomous electronic toll collection systems. Specifies data syntax and semantics for verifying toll obligations and OBE performance without writing to vehicle systems.

novelty_note:
  Specialized domain standard for toll systems; compliance checking communication is specific but not broadly innovative

relevance_note:
  Relevant to autonomous toll systems but narrow applicability; not directly relevant to general autonomous agents or AI systems


draft_name: iso-13141-2015
novelty_note: Domain-specific standard for toll system localization; technical but incremental contribution
maturity_note: Published ISO standard from 2015; fully mature specification
momentum_note: Mature standard with no indication of active development or updates
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:12:29.343115+00:00
summary:
  Establishes short-range communication requirements for localization augmentation in autonomous electronic fee collection systems. Specifies location/heading information provision and security mechanisms to protect OBE from false roadside equipment manipulation.

overlap_note:
  Some overlap with iso-12813-2015 in EFC context and DSRC communication; both are toll-specific standards

relevance_note:
  Relevant to autonomous vehicle localization in toll contexts but limited broader applicability to general autonomous systems


draft_name: iso-tr-15801-2017
maturity_note: Published technical report from 2017; mature but broader scope allows for continued evolution
overlap_note: Unique focus on trustworthy information storage; minimal overlap with other documents
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:12:29.353169+00:00
summary:
  Provides recommendations for implementing information management systems that store and provide electronically stored information in trustworthy and reliable manner over time. Focuses on policies, procedures, technology and audit requirements to maintain ESI trustworthiness.

novelty_note:
  General guidance document for ESI trustworthiness; not novel methodology but practical recommendations

momentum_note:
  Published TR with no clear update trajectory; moderate relevance suggests potential for incremental updates

relevance_note:
  Relevant to autonomous agent data integrity and audit requirements but not specific to agent systems


draft_name: iso-pwi-20531
novelty_note: Standard test methodology for autonomous vehicle safety; important but not conceptually novel
maturity_note: PWI (Preliminary Work Item) status indicates early development stage; not yet published
overlap_note: Unique focus on braking system performance testing; no meaningful overlap with other documents
momentum_note: Active development as PWI suggests ongoing committee work and momentum
relevance_note: Relevant to autonomous vehicle safety validation but narrow focus on specific subsystem
categories: ["Policy/governance"]
rated_at: 2026-03-08T17:12:29.362588+00:00
summary:
  Specifies test methods to evaluate the performance of autonomous braking systems in road vehicles. Addresses autonomous vehicle safety validation.


draft_name: iso-iec-20546-2019
maturity_note: Published ISO/IEC standard from 2019; mature specification with established vocabulary
overlap_note: Unique focus on big data terminology; minimal overlap with other specialized domain standards
momentum_note: Published standard with vocabulary focus suggests stable but potentially slow update cycle
categories: ["Data formats/interop"]
rated_at: 2026-03-08T17:12:29.371104+00:00
summary:
  Provides terminology, definitions, and conceptual overview of big data field. Establishes foundational vocabulary for big data standards and clarifies relationship between big data and related technical areas.

novelty_note:
  Foundational vocabulary work provides useful standardization but represents incremental consolidation rather than novel concepts

relevance_note:
  Relevant to autonomous systems handling large data volumes but is generic data terminology rather than agent-specific


draft_name: iso-pwi-20554
maturity_note: PWI stage indicates early development; builds on established ISO/TC 22 vehicle safety framework
overlap_note: Minimal overlap with other drafts; specific technical focus on braking validation
momentum_note: Early stage (PWI) with unclear timeline; represents ongoing standardization effort
relevance_note: Directly relevant to AV safety assurance and regulatory compliance requirements
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:12:40.111359+00:00
summary:
  Establishes test methods for evaluating autonomous vehicle braking system performance. Focuses on safety validation and standardized testing protocols for AV critical systems.

novelty_note:
  Incremental standards work on AV safety testing; addresses known gap in braking system evaluation methodology


draft_name: iso-pwi-20800
maturity_note: PWI stage; represents niche standardization work in underwater acoustics domain
momentum_note: Early stage development with limited visibility; specialized application area
relevance_note: Low relevance to broader autonomous vehicle/agent ecosystem; highly specialized domain
categories: ["Data formats/interop", "Autonomous netops"]
rated_at: 2026-03-08T17:12:40.122466+00:00
summary:
  Specifies calibration methods for autonomous underwater acoustic recording systems. Establishes metrological standards for autonomous sensor systems in marine environments.

novelty_note:
  Domain-specific technical standard; limited novelty beyond applying existing calibration principles to autonomous recorders

overlap_note:
  Unique focus on underwater acoustic systems; minimal overlap with other autonomous vehicle/agent standards


draft_name: iso-37168-2022
maturity_note: Published standard (2022); represents mature guidance from ISO standardization process
relevance_note: Highly relevant to autonomous vehicle deployment strategy and multi-stakeholder coordination
categories: ["Policy/governance", "Agent discovery/reg", "Human-agent interaction"]
rated_at: 2026-03-08T17:12:40.133080+00:00
summary:
  Provides implementation guidance for Electric, Connected, and Autonomous Vehicles (eCAVs) in on-demand shared mobility services. Focuses on staged deployment for responsive transportation and delivery.

novelty_note:
  Addresses emerging use case of shared autonomous vehicles for responsive services; integrates electrification and connectivity dimensions

overlap_note:
  Moderate overlap with ISO 37181; distinguished by focus on shared on-demand services vs. public road autonomous vehicles

momentum_note:
  Recently published with clear governance framework; active standardization momentum in smart transportation


draft_name: iso-37181-2022
maturity_note: Published standard (2022); mature, consensus-based guidance from international committee
categories: ["Policy/governance", "Agent discovery/reg", "Human-agent interaction"]
rated_at: 2026-03-08T17:12:40.142847+00:00
summary:
  Establishes guidelines for introducing and organizing autonomous vehicles on public roads. Addresses safety enhancement, urban challenges, and deployment as operational systems.

novelty_note:
  Comprehensive framework covering governance, safety, and organizational aspects of AV deployment; complements technical standards

overlap_note:
  Moderate overlap with ISO 37168; distinguished by focus on public road operations vs. shared on-demand services

momentum_note:
  Recently published with active ISO/TC 211 engagement; strong momentum for smart city infrastructure standards

relevance_note:
  Highly relevant to autonomous vehicle governance, policy frameworks, and multi-stakeholder coordination


draft_name: iso-12813-2015-amd-1-2017
maturity_note: Published amendment (2017); mature, established standard with minor updates for autonomy
overlap_note: Unique focus on fee collection protocols; minimal overlap with other autonomous vehicle standards
momentum_note: Established standard with amendment; moderate momentum in tolling/fee collection domain
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:12:40.152711+00:00
summary:
  Amendment to electronic fee collection standard addressing compliance communication for autonomous systems. Extends fee collection protocols to support autonomous vehicle integration.

novelty_note:
  Incremental amendment applying existing fee collection standards to autonomous systems; limited conceptual novelty

relevance_note:
  Specialized relevance to tolling systems; limited application to broader autonomous vehicle ecosystem


draft_name: iso-13141-2015-amd-1-2017
maturity_note: Published ISO standard amendment with full maturity and regulatory implementation
overlap_note: Minimal overlap; specialized domain-specific amendment
momentum_note: Amendment to legacy standard; limited emerging activity in this specific area
categories: ["Autonomous netops", "Data formats/interop", "A2A protocols"]
rated_at: 2026-03-08T17:12:49.942945+00:00
summary:
  Amendment to ISO 13141 addressing localization augmentation communication for autonomous systems in electronic fee collection. Focuses on enhancing communication protocols for location-based services in tolling systems.

novelty_note:
  Narrow amendment to existing standard; incremental improvements to established fee collection systems

relevance_note:
  Highly specialized application; limited relevance to broader autonomous systems or AI agent frameworks


draft_name: iso-iec-dis-30754
relevance_note: Relevant to agent trust, autonomous systems governance, and AI safety considerations
categories: ["Policy/governance", "AI safety/alignment", "Agent identity/auth"]
rated_at: 2026-03-08T17:12:49.954388+00:00
summary:
  Draft specification for software trustworthiness governance and management covering ISO/IEC standards. Addresses trust frameworks and governance structures for software systems.

novelty_note:
  Emerging standard addressing growing concerns around software trust and governance; moderate novelty in formalization

maturity_note:
  DIS (Draft International Standard) stage; still under development with governance framework maturation needed

overlap_note:
  Some overlap with AI safety/alignment and agent identity concerns; governance approaches applicable across domains

momentum_note:
  Active development in trustworthiness domain; moderate momentum in software governance standardization


draft_name: iso-iec-tr-20547-1-2020
novelty_note: Mature framework with established reference architecture; application guidance adds moderate value
maturity_note: Published technical report with solid foundational maturity; application methodology well-developed
overlap_note: Significant overlap with Part 3 reference architecture; complementary framework documentation
momentum_note: Stable technical report; moderate ongoing adoption in big data ecosystem
relevance_note: Relevant to data-intensive autonomous systems and multi-agent data processing architectures
categories: ["Data formats/interop", "ML traffic mgmt", "Autonomous netops"]
rated_at: 2026-03-08T17:12:49.964429+00:00
summary:
  Technical report describing the big data reference architecture framework and application methodology. Provides guidance on how organizations can apply the BDRA to their specific domains.


draft_name: iso-iec-tr-20547-2-2018
novelty_note: Practical use case documentation; moderate novelty in synthesizing requirements across domains
maturity_note: Published technical report with well-documented use cases and derived requirements
overlap_note: Companion to reference architecture parts; heavy interdependency with Part 3 specifications
momentum_note: Established technical report; steady reference in big data implementation guidance
relevance_note: Relevant to understanding agent-based big data processing and multi-stakeholder systems
categories: ["Data formats/interop", "ML traffic mgmt", "Autonomous netops"]
rated_at: 2026-03-08T17:12:49.974188+00:00
summary:
  Technical report providing concrete big data use cases across application domains with derived technical requirements. Offers practical examples and implementation considerations.


draft_name: iso-iec-20547-3-2020
novelty_note: Established reference architecture; incremental improvements over prior versions
maturity_note: Published ISO standard with comprehensive architectural specification and maturity
overlap_note: Core architecture document with heavy overlap to Parts 1 and 2 as companion specifications
momentum_note: Published standard with solid adoption; continued relevance to big data ecosystem standardization
categories: ["Data formats/interop", "Agent discovery/reg", "Autonomous netops", "ML traffic mgmt"]
rated_at: 2026-03-08T17:12:49.983279+00:00
summary:
  ISO standard specifying the big data reference architecture with user and functional viewpoints. Defines architectural layers, component classes, roles, and relationships within big data ecosystems.

relevance_note:
  Highly relevant to multi-agent systems, data interoperability, and autonomous data processing architectures


draft_name: iso-pwi-22133-1
maturity_note: Early stage PWI (Preliminary Work Item); still in pre-standard development
momentum_note: PWI status suggests early momentum; part of coordinated multi-part standard effort
categories: ["A2A protocols", "Data formats/interop", "Autonomous netops"]
rated_at: 2026-03-08T17:13:01.411213+00:00
summary:
  Defines communication protocols and interfaces for monitoring and controlling test objects in active safety and autonomous vehicle testing. Establishes standardized ways for test systems to interact with vehicles under evaluation.

novelty_note:
  Foundational infrastructure work; communication protocols are well-established domain but application to AV testing is specialized

overlap_note:
  Moderate overlap with ISO 22133-2 (same series) and general vehicle testing standards; communication protocols are commoditized

relevance_note:
  Directly relevant to AV testing infrastructure; essential for standardizing test environment interactions


draft_name: iso-pwi-22133-2
maturity_note: PWI status indicates early development stage; companion to Part 1
momentum_note: Part of coordinated standard development; momentum tied to broader AV testing standardization push
categories: ["Data formats/interop", "Autonomous netops"]
rated_at: 2026-03-08T17:13:01.421238+00:00
summary:
  Specifies test scenario description formats for active safety and autonomous vehicle testing. Provides standardized ways to represent, encode, and communicate test scenarios.

novelty_note:
  Addresses a specific gap in AV testing standardization; scenario representation formats are emerging but not yet mature

overlap_note:
  Complements ISO 22133-1 closely; overlaps with scenario definition approaches in simulation and testing domains

relevance_note:
  Critical for AV testing reproducibility and validation; essential for interoperability across test platforms


draft_name: iso-iec-tr-20547-5-2018
maturity_note: Published technical report; mature document but snapshot in time from 2018
momentum_note: Published 2018; limited current momentum as roadmap document; value decreases over time
categories: ["Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:13:01.430777+00:00
summary:
  Technical report mapping existing and emerging big data standards, identifying gaps and priorities for future standards development. Provides roadmap for big data standardization across information technology.

novelty_note:
  Meta-level standards analysis; provides perspective but not directly advancing standards; published 2018 (aging)

overlap_note:
  Heavy overlap with other standards roadmap efforts; big data standardization is heavily analyzed across multiple bodies

relevance_note:
  Peripherally relevant to AV/AI; big data is enabling technology but not core to autonomous agent protocols or testing


draft_name: iso-22733-1-2021
maturity_note: Published standard (2021); mature and implemented; represents mature consensus on AEBS testing
categories: ["AI safety/alignment", "Autonomous netops"]
rated_at: 2026-03-08T17:13:01.439559+00:00
summary:
  Specifies test methodology for evaluating autonomous emergency braking system performance in car-to-car collision scenarios. Defines procedures, scenarios, and metrics for AEBS/DBS evaluation.

novelty_note:
  Addresses specific safety-critical application; practical test methodology with concrete scenario design; novel contribution to AV safety validation

overlap_note:
  Highly specific to AEBS testing; limited overlap with other standards except adjacent AV safety standards

momentum_note:
  Published standard with implementation track record; part of growing AV safety standardization ecosystem

relevance_note:
  Directly critical to AV safety validation and real-world deployment; core safety-critical application


draft_name: iso-12813-2015-cd-amd-2
maturity_note: Amendment to 2015 standard (CD stage); older baseline but amendment indicates ongoing refinement
momentum_note: Amendment to aging standard; limited visibility of active momentum in autonomous fee collection
categories: ["A2A protocols", "Data formats/interop"]
rated_at: 2026-03-08T17:13:01.447831+00:00
summary:
  Amendment 2 to electronic fee collection standard addressing compliance check communication for autonomous systems. Updates communication protocols for tolling/payment systems interacting with autonomous vehicles.

novelty_note:
  Incremental amendment to existing standard; applies established e-payment communication to autonomous context but represents narrow scope

overlap_note:
  Heavy overlap with general electronic toll collection standards; autonomous systems aspect is minor modification to existing domain

relevance_note:
  Narrowly relevant to specific AV use case (tolling); not core to safety, testing, or agent infrastructure


draft_name: iso-12813-2019
novelty_note: Narrow domain-specific standard for toll system compliance; limited cross-domain applicability
maturity_note: Published standard with clear specifications and requirements
overlap_note: Minimal overlap; specific to toll collection domain rather than general autonomous systems
momentum_note: Established standard but limited ongoing development signals
relevance_note: Relevant only to toll/fee collection systems; not broadly applicable to general autonomous systems
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:13:12.062269+00:00
summary:
  Defines short-range communication protocols for compliance checking between vehicle on-board equipment and roadside interrogators in autonomous electronic toll collection systems. Specifies data syntax, semantics, and attributes for verifying vehicle road usage and OBE functionality without writing to OBE data.


draft_name: iso-17757-2019
maturity_note: Published standard with established safety criteria and guidance
overlap_note: Safety requirements are domain-specific; limited overlap with other autonomous domains
momentum_note: Mature standard with limited signals of active evolution
relevance_note: Relevant to specialized industrial autonomous systems but not general-purpose autonomous agents
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:13:12.073217+00:00
summary:
  Provides comprehensive safety requirements for autonomous and semi-autonomous machines used in earth-moving and mining operations, covering hardware, software, systems, and infrastructure throughout the machine lifecycle.

novelty_note:
  Industry-specific safety standard for heavy machinery; complements rather than advances general autonomous systems theory


draft_name: iso-iec-np-23614
novelty_note: Early-stage proposal with minimal available information; foundational data structure work
maturity_note: New proposal stage (NP); no published content or specifications available
momentum_note: Early-stage development with unclear momentum
categories: ["Agent discovery/reg", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:13:12.083054+00:00
summary:
  Nascent proposal for establishing a framework standard for Knowledge Graphs under ISO/IEC JTC 1/SC 42.

overlap_note:
  Knowledge graphs are foundational infrastructure potentially overlapping with agent discovery, identity, and data interoperability

relevance_note:
  Potentially relevant as foundational infrastructure for autonomous agent systems but highly abstract at this stage


draft_name: iso-iec-np-23615
maturity_note: New proposal stage (NP); no published specifications available
momentum_note: Early-stage; momentum unclear
categories: ["Model serving/inference", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:13:12.093371+00:00
summary:
  Nascent proposal for standardizing neural network representation formats and model compression techniques under ISO/IEC JTC 1/SC 42.

novelty_note:
  Early-stage proposal addressing ML model efficiency and portability; incremental advance in model standardization

overlap_note:
  Model representation and compression overlap with model serving, inference optimization, and data interoperability

relevance_note:
  Relevant to autonomous agents using neural networks for perception/decision-making but at formative stage


draft_name: iso-tr-9241-810-2020
maturity_note: Published technical report with structured guidance; positions as foundation for future standards
momentum_note: Published report suggests active standards development in ergonomics/HCI domain
categories: ["Human-agent interaction", "AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:12.103591+00:00
summary:
  Technical report addressing ergonomic and interaction requirements for robotic, intelligent, and autonomous systems (RIA), covering physically embodied systems, embedded environmental systems, software agents, and broader sociotechnical impacts on users and society.

novelty_note:
  Broad multidisciplinary approach integrating human factors with diverse RIA categories; bridges technical and sociotechnical domains

overlap_note:
  Human-agent interaction focus is distinct from protocol/technical standards; limited overlap with other drafts

relevance_note:
  Highly relevant to autonomous systems design; addresses critical human factors often overlooked in technical standards


draft_name: iso-23725-2024
maturity_note: Published ISO standard (2024) with mature specification of interfaces and requirements
momentum_note: Recently published international standard indicates strong industry adoption momentum
relevance_note: Directly relevant to autonomous system interoperability and operational coordination
categories: ["A2A protocols", "Data formats/interop", "ML traffic mgmt"]
rated_at: 2026-03-08T17:13:21.981840+00:00
summary:
  Defines interoperability interfaces between fleet management and autonomous haulage systems in surface mining, covering communication protocols, message structures, telemetry, and task coordination. Establishes standards for real-time system communication and data exchange.

novelty_note:
  Domain-specific standardization of autonomous vehicle coordination in industrial settings; concrete protocol and message structure definitions

overlap_note:
  Some overlap with general A2A protocols and data formats, but highly specialized to mining/haulage domain


draft_name: iso-ts-23860-2022
maturity_note: Published technical specification (2022); primarily definitional rather than prescriptive
overlap_note: Terminology work overlaps with broader autonomous system standards but specific to maritime domain
categories: ["Policy/governance", "Autonomous netops", "Other AI/agent"]
rated_at: 2026-03-08T17:13:21.994122+00:00
summary:
  Defines terminology and vocabulary for autonomous ship systems including Maritime Autonomous Surface Ships (MASS) as defined by IMO, applicable to both maritime and inland waterway vessels.

novelty_note:
  Standardized terminology development for maritime autonomous systems; bridges IMO regulatory framework with technical standards

momentum_note:
  Aligns with IMO's regulatory work on autonomous vessels, indicating sustained maritime industry interest

relevance_note:
  Relevant for establishing common terminology but limited direct applicability to technical implementation


draft_name: iso-iec-tr-24027-2021
maturity_note: Technical report (2021) rather than full standard; addresses emerging concerns in AI safety
overlap_note: Addresses fundamental AI safety concern with limited overlap to domain-specific autonomous systems
momentum_note: Active focus area with ongoing regulatory and industry emphasis on responsible AI
relevance_note: Critical for safe autonomous system deployment; applies broadly across agent implementations
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:13:22.004131+00:00
summary:
  Addresses bias in AI systems and AI-aided decision-making across all lifecycle phases from data collection to deployment, providing measurement techniques and assessment methods for bias vulnerabilities.

novelty_note:
  Comprehensive treatment of bias assessment across complete AI lifecycle; practical measurement and mitigation techniques


draft_name: iso-tr-24291-2021
novelty_note: Domain categorization of existing ML applications; limited technical novelty in methodology
maturity_note: Technical report providing applied examples rather than normative standards or frameworks
overlap_note: Heavy overlap with general ML application frameworks; medical domain specialization
momentum_note: Moderate momentum in medical AI applications but limited evidence of transformative impact
relevance_note: Limited relevance to autonomous agent systems and interoperability concerns
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:13:22.013310+00:00
summary:
  Categorizes use cases and clinical applications of machine learning in medical domains (radiology, pathology, surgery, etc.), excluding data collection, model training, and non-clinical research.


draft_name: iso-iec-24668-2022
maturity_note: Broad applicability but not specifically tied to autonomous or agent systems
overlap_note: Overlaps with general data management and organizational governance frameworks; not agent-specific
relevance_note: Minimally relevant to autonomous agent interoperability; tangential to autonomous netops
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:13:22.022735+00:00
summary:
  Provides organizational process management framework for big data analytics covering stakeholder coordination, competency development, data management, analytics development, and technology integration.

novelty_note:
  Generic process framework for big data analytics; applicable across industries but lacks agent/autonomous system specificity


draft_name: iso-iec-15938-17-2022
maturity_note: Published ISO/IEC standard with complete specification and well-defined scope boundaries
momentum_note: Stable published standard but niche application in multimedia content description
categories: ["Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:13:33.771640+00:00
summary:
  Specifies Neural Network Coding (NNC) as a compressed representation of trained neural network parameters and weights. Establishes compression methods including sparsification, quantization, and entropy coding for efficient neural network exchange and storage.

novelty_note:
  Focused technical compression standard; incremental contribution to existing multimedia framework rather than novel approach

overlap_note:
  Minimal overlap; specialized compression format not directly related to interoperability protocols or agent systems

relevance_note:
  Limited relevance to autonomous agent communication; primarily focused on model representation efficiency


draft_name: iso-iec-tr-24368-2022
overlap_note: Unique scope covering ethical dimensions; minimal overlap with technical interoperability standards
momentum_note: Recent publication (2022) reflecting growing momentum in AI governance and ethics standardization
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:13:33.782442+00:00
summary:
  Provides high-level overview of AI ethical and societal concerns for technologists, regulators, and society. Covers principles, processes, methods, and references related international standards addressing AI ethics issues.

novelty_note:
  Broad overview document lacking technical depth; synthesizes existing ethical frameworks rather than proposing new approaches

maturity_note:
  Published technical report establishing baseline understanding; framework-level maturity without implementation specifications

relevance_note:
  Relevant to policy and governance aspects of autonomous systems but not directly addressing technical interoperability


draft_name: iso-iec-tr-24372-2021
momentum_note: Foundational reference document with steady relevance but no significant momentum indicators
relevance_note: General background on AI systems; indirect relevance to autonomous agent interoperability specifics
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:13:33.791963+00:00
summary:
  Provides overview of computational approaches and algorithms used in AI systems, describing main characteristics and approaches with reference to use cases. Intended as informational reference on AI system implementations.

novelty_note:
  Descriptive survey of existing computational methods; limited novel insight beyond state-of-art cataloging

maturity_note:
  Published technical report with informational scope; lacks formal specification or normative requirements

overlap_note:
  Broad coverage of AI approaches but minimal overlap with specific interoperability or agent protocol standards


draft_name: iso-ts-22133-2023
categories: ["A2A protocols", "Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:13:33.802412+00:00
summary:
  Specifies requirements, procedures, and message formats for controlling and monitoring test objects used in active safety and autonomous vehicle testing. Defines interoperable communication protocol for multi-vendor test environments.

novelty_note:
  Focused on test infrastructure; technical specification addresses known domain but specific to testing context rather than operational autonomy

maturity_note:
  Published technical specification with detailed functional requirements and protocol definitions for test environments

overlap_note:
  Some overlap with autonomous vehicle communication but specialized to testing/validation rather than operational interoperability

momentum_note:
  Recent publication (2023) in active domain of autonomous vehicle development and testing infrastructure

relevance_note:
  Highly relevant to autonomous systems testing and control; addresses multi-vendor interoperability in controlled environments


draft_name: iso-pwi-3510
categories: ["A2A protocols", "Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:13:33.812426+00:00
summary:
  Specification for interoperability of teleoperated, autonomous, and manned mining equipment under ISO/TC 82/SC 8. Addresses integration of multiple equipment types in mining operations.

novelty_note:
  Domain-specific interoperability standard; applies established interoperability principles to mining sector without apparent methodological innovation

maturity_note:
  Pre-publication work item (PWI) status indicates early development stage with incomplete specification

overlap_note:
  Significant overlap with autonomous vehicle and multi-agent interoperability standards; addresses similar integration challenges in different domain

momentum_note:
  Early-stage work item; momentum unclear given lack of publication timeline or detailed specification availability

relevance_note:
  Relevant to autonomous/teleoperated equipment interoperability but domain-specific to mining applications


draft_name: iso-iec-ts-4213-2022
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:45.342211+00:00
summary:
  Specifies methodologies for measuring classification performance of machine learning models, systems and algorithms. Provides standardized approaches to ML model evaluation metrics and assessment procedures.

novelty_note:
  Classification performance assessment is well-established; primarily codifies existing practices rather than introducing novel concepts

maturity_note:
  Published standard with clear methodological scope; mature application of established ML evaluation techniques

overlap_note:
  Moderate overlap with ISO/IEC 25059 on quality evaluation; complements but doesn't heavily duplicate other drafts

momentum_note:
  Standard publication indicates stability; limited momentum as it addresses foundational rather than emerging concerns

relevance_note:
  Highly relevant for ML practitioners needing standardized evaluation frameworks; essential for quality assurance


draft_name: iso-iec-24029-2-2023
relevance_note: Highly relevant for safety-critical AI systems; addresses critical need for robustness guarantees
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:45.352330+00:00
summary:
  Provides methodology for using formal methods to assess robustness properties of neural networks. Focuses on selection, application and management of formal verification techniques for proving robustness.

novelty_note:
  Formal verification applied to neural network robustness is relatively novel; brings rigorous mathematical approaches to an emerging concern

maturity_note:
  Recent publication but formal methods for neural networks remain technically immature; practical application still developing

overlap_note:
  Unique focus on formal methods; minimal overlap with other documents though complements ISO/IEC 25059 quality framework

momentum_note:
  Growing momentum in AI safety community; formal verification is increasingly prioritized for critical applications


draft_name: iso-iec-tr-27563-2023
overlap_note: Moderate overlap with ISO/IEC 25059 on quality aspects; complements broader governance frameworks
momentum_note: Steady momentum as security/privacy concerns in AI continue to grow in importance
categories: ["Policy/governance", "Human-agent interaction", "Other AI/agent"]
rated_at: 2026-03-08T17:13:45.371880+00:00
summary:
  Outlines best practices for assessing security and privacy in AI use cases, covering overall system assessment, security/privacy concerns, and related risk management. References ISO/IEC TR 24030 AI use cases.

novelty_note:
  Security/privacy frameworks exist; applies established practices to AI context rather than introducing fundamentally new approaches

maturity_note:
  Recent technical report with comprehensive coverage; mature application of security/privacy principles to AI

relevance_note:
  Critical relevance given regulatory emphasis on AI security and privacy; directly addresses stakeholder concerns


draft_name: iso-ts-42501-2022
maturity_note: Standard published but scope is general; implementation specificity remains limited
momentum_note: Limited momentum; sharing economy governance is maturing but not an active innovation area
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:13:45.380204+00:00
summary:
  Specifies general trustworthiness and safety requirements for digital platform operators in the sharing economy. Provides guidance beneficial for system development despite not covering specific system requirements.

novelty_note:
  Sharing economy platforms are well-established; requirements are incremental refinements of existing trust/safety principles rather than novel

overlap_note:
  Significant conceptual overlap with ISO/IEC 25059 quality model and ISO/IEC TR 27563 on trustworthiness; focuses on broader platform governance

relevance_note:
  Marginal relevance to core AI/agent standards; applies more broadly to digital platforms than AI-specific systems


draft_name: iso-iec-25059-2023
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:45.390049+00:00
summary:
  Outlines a quality model for AI systems as an extension to SQuaRE standards. Defines characteristics and sub-characteristics for consistently specifying, measuring and evaluating AI system quality.

novelty_note:
  Quality models for general software exist; AI-specific extension is incremental; characteristics largely adapt existing SQuaRE framework

maturity_note:
  Recently published with structured methodology; builds on mature SQuaRE standards for clear applicability

overlap_note:
  Overlaps with ISO/IEC TS 4213 on evaluation; complements ISO/IEC TR 27563 on quality aspects; provides overarching framework

momentum_note:
  Solid momentum as AI quality assessment becomes standardization priority; builds on established SQuaRE ecosystem

relevance_note:
  Highly relevant as foundational quality framework for AI systems; essential reference for comprehensive evaluation


draft_name: iso-iec-pwi-5096
maturity_note: PWI (Preliminary Work Item) stage indicates very early development; concept still being defined
momentum_note: Early stage suggests limited momentum; awaiting progression through ISO committee process
relevance_note: High relevance to AI-enabled network operations and autonomous systems
categories: ["Autonomous netops", "ML traffic mgmt", "Policy/governance"]
rated_at: 2026-03-08T17:13:55.273233+00:00
summary:
  Early-stage ISO standard for AI-enabled networking. Establishes foundational concepts and requirements for integrating artificial intelligence into network management and operations.

novelty_note:
  Moderately novel approach to standardizing AI in networking domain; builds on existing network standards but adds AI dimension

overlap_note:
  Moderate overlap with autonomous netops and ML traffic management concepts; distinct from most other drafts


draft_name: iso-iec-wd-ts-23220-6
maturity_note: WD (Working Draft) stage; moderately developed but still in active revision
momentum_note: Moderate momentum as part of active ISO/IEC JTC 1/SC 17 work on identity standards
relevance_note: Relevant to agent authentication and identity management in distributed systems
categories: ["Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:13:55.282786+00:00
summary:
  Working draft standard for mobile identity management security devices. Specifies mechanisms for certifying trustworthiness of secure areas in personal identification systems via mobile devices.

novelty_note:
  Incremental addition to existing identity management standards; focuses on certification mechanisms rather than novel concepts

overlap_note:
  High overlap with agent identity/authentication standards; heavy focus on security credentials and device trust


draft_name: iso-tr-22100-5-2021
maturity_note: Published TR (Technical Report) with clear maturity; established guidance document from 2021
momentum_note: Established momentum as published standard; cited reference in AI safety domain
relevance_note: High relevance to AI safety and alignment, particularly in industrial/operational contexts
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:13:55.292030+00:00
summary:
  Published technical report addressing safety implications of AI/ML in machinery and industrial systems. Provides guidance on incorporating AI hazard analysis into machinery safety risk assessments.

novelty_note:
  Novel application of safety methodology to AI/ML systems; extends ISO 12100 safety framework to AI domain

overlap_note:
  Minimal overlap with other drafts; unique focus on machinery safety rather than networking or identity


draft_name: iso-iec-5259-1-2024
maturity_note: Published in 2024; mature and current standard with formal status
momentum_note: High momentum as recently published (July 2024) formal ISO/IEC standard
relevance_note: High relevance to ML systems quality, data governance, and interoperability standards
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:55.301720+00:00
summary:
  Published foundational standard for data quality in analytics and ML. Part 1 provides terminology, overview, and use cases for the ISO/IEC 5259 data quality series.

novelty_note:
  Moderately novel systematization of data quality concepts for ML; establishes common terminology and framework

overlap_note:
  Minimal overlap with other drafts; foundational data quality focus distinct from networking/identity domains


draft_name: iso-iec-5259-3-2024
maturity_note: Published in 2024; fully mature formal ISO/IEC standard with clear requirements and guidance
overlap_note: Unique focus on data quality management process requirements; minimal overlap with other drafts
momentum_note: High momentum as recently published formal standard complementing Part 1
relevance_note: High relevance to ML data governance, quality management, and operational standards
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:13:55.310688+00:00
summary:
  Published requirements standard for data quality management in analytics and ML. Specifies generic requirements and guidance for establishing and maintaining data quality processes applicable to all organizations.

novelty_note:
  Moderately novel generic framework for data quality management; extends Part 1 with operational requirements and guidance


draft_name: iso-iec-5259-4-2024
maturity_note: Published ISO standard (July 2024) with mature framework; represents consensus best practices.
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:06.643554+00:00
summary:
  Establishes organizational approaches for ensuring data quality in ML training and evaluation across supervised, unsupervised, and semi-supervised learning. Provides guidance on data labeling processes and quality frameworks applicable to organizations of any size.

novelty_note:
  Data quality for ML is well-established; this standard formalizes existing practices rather than introducing novel concepts.

overlap_note:
  Overlaps with general ML quality assurance literature and prior ISO/IEC AI standards on data handling.

momentum_note:
  Recent publication and part of active ISO/IEC 5259 series indicates ongoing standardization momentum in data quality.

relevance_note:
  Highly relevant for any ML-based agent or AI system requiring reliable training data and quality assurance.


draft_name: iso-iec-5392-2024
maturity_note: Published ISO standard (March 2024); represents mature consensus on KE reference models.
momentum_note: Published as formal standard but incremental to existing KE literature.
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:06.653385+00:00
summary:
  Defines reference architecture for knowledge engineering in AI, including roles, activities, components, layers and relationships. Provides common vocabulary and systemic framework for KE systems.

novelty_note:
  Knowledge engineering architectures are established discipline; standard consolidates rather than innovates.

overlap_note:
  Aligns with existing knowledge representation and ontology standards; provides standardized terminology.

relevance_note:
  Moderate relevance; applicable to AI systems requiring knowledge representation but not directly addressing agent protocols or interoperability.


draft_name: iso-iec-tr-5469-2024
overlap_note: Limited overlap; safety-critical AI is specialized domain with fewer parallel standards.
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:06.662146+00:00
summary:
  Technical report addressing functional safety integration with AI systems, including AI in safety-critical functions, non-AI safeguards for AI systems, and AI-assisted safety design. Covers risk factors, properties, and available methods.

novelty_note:
  Intersection of AI and functional safety is emerging; addresses novel challenges of AI in safety-critical applications.

maturity_note:
  Published as technical report (January 2024) rather than full standard; indicates developing maturity of this domain.

momentum_note:
  TR publication suggests standardization work in progress; moderate momentum in safety-AI integration.

relevance_note:
  Highly relevant for autonomous systems, critical infrastructure agents, and any safety-dependent AI deployment.


draft_name: iso-np-ts-18759
novelty_note: Document storage is mature domain; trustworthiness focus is incremental enhancement.
momentum_note: Early-stage proposal with no publication date indicates nascent momentum.
relevance_note: Low relevance to agent systems, AI protocols, or interoperability; focused on document storage.
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:14:06.670971+00:00
summary:
  New project proposing technical specification for trustworthy storage systems covering functional and technical requirements for document management.

maturity_note:
  New project proposal stage (no published date); very early development with minimal concrete content.

overlap_note:
  Heavy overlap with existing document management standards (ISO 22733 series); incremental trustworthiness requirements.


draft_name: iso-22733-2-2023
maturity_note: Published ISO standard (November 2023); represents mature testing consensus.
overlap_note: Part of ISO 22733 series; overlap with vehicle safety testing standards.
momentum_note: Recent publication indicates active standardization of autonomous vehicle safety testing.
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:06.680062+00:00
summary:
  Specifies test methods for evaluating autonomous emergency braking systems (AEBS) in car-to-pedestrian collision scenarios. Covers performance evaluation in both longitudinal and perpendicular pedestrian approach situations.

novelty_note:
  Testing methodology for AEBS is established domain; this part extends existing framework to pedestrian scenarios.

relevance_note:
  Moderate relevance for autonomous vehicle agents and safety validation; limited applicability beyond vehicular domain.


draft_name: iso-iec-ts-5723-2022
maturity_note: Published standard (2022) with stable maturity; forms basis for derivative standards
overlap_note: Heavy overlap with trust/security frameworks; complementary to ISO/IEC 5957 and 6254
momentum_note: Established standard with slow evolution; foundational rather than cutting-edge
relevance_note: Relevant for AI governance frameworks; applies broadly to systems beyond AI
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:16.334487+00:00
summary:
  Defines trustworthiness for systems and services with characteristic definitions. Establishes foundational vocabulary for trust concepts in IT systems.

novelty_note:
  Vocabulary standardization is incremental; trustworthiness is well-explored but formalization adds clarity


draft_name: iso-iec-5259-2-2024
novelty_note: Data quality metrics are established domain; part 2 extends part 1 with operational measures
maturity_note: Recent publication (2024) with comprehensive, actionable specifications
overlap_note: Focused niche on data quality for ML; minimal overlap with other listed standards
momentum_note: Recent release suggests active standardization progress in data quality domain
relevance_note: Highly relevant for ML system quality; essential for responsible AI development
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:16.346162+00:00
summary:
  Specifies data quality models, measures, and reporting guidance for analytics and ML. Addresses data quality objectives across organizations.


draft_name: iso-iec-pwi-5957
novelty_note: Reference architecture for trustworthiness is novel; advances beyond vocabulary definitions
maturity_note: Pre-publication PWI status; early development with no publication date; immature
overlap_note: Will complement ISO/IEC TS 5723; overlaps conceptually with trustworthiness frameworks
momentum_note: Early stage development; no publication momentum visible yet
relevance_note: High relevance for AI system architecture; foundational for trustworthy AI deployment
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:16.356347+00:00
summary:
  Developing reference architecture for trustworthiness systems. Currently in pre-publication working draft stage.


draft_name: iso-iec-ts-6254-2025
maturity_note: Published technical specification (2025); comprehensive but emerging domain maturity
momentum_note: Recent 2025 publication indicates strong momentum in AI transparency standardization
relevance_note: Highly critical for AI safety, regulatory compliance, and human-agent trust
categories: ["AI safety/alignment", "Human-agent interaction", "Policy/governance"]
rated_at: 2026-03-08T17:14:16.365715+00:00
summary:
  Provides approaches for achieving explainability and interpretability of ML and AI systems across lifecycle. Addresses stakeholder objectives including academia, industry, and policymakers.

novelty_note:
  Explainability guidance operationalizes interpretability; extends beyond theory with practical methods

overlap_note:
  Focused on explainability/interpretability; minimal overlap with data quality or architecture standards


draft_name: iso-ts-18759-2022
novelty_note: Storage security is established field; requirements are standard practice formalization
maturity_note: Published standard (2022) with mature, practical specifications
overlap_note: Trustworthiness dimension overlaps with ISO/IEC TS 5723; otherwise specialized to storage
momentum_note: Established standard with narrow application scope; stable rather than dynamic
relevance_note: Relevant for data preservation in ML pipelines; primarily storage-focused rather than AI-specific
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:14:16.376575+00:00
summary:
  Specifies functional and technology-neutral requirements for trustworthy storage systems protecting electronically stored information. Addresses immutability, authenticity, and security throughout information lifecycle.


draft_name: iso-iec-ts-25058-2024
maturity_note: Published 2024 technical specification with mature quality evaluation concepts adapted for AI
overlap_note: Minimal overlap with autonomous machinery standards; unique focus on AI system quality assessment
momentum_note: Strong momentum as AI quality standards are actively being developed across ISO/IEC
relevance_note: Highly relevant for any AI system evaluation; foundational for quality assurance practices
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:14:26.870323+00:00
summary:
  Provides guidance for evaluating artificial intelligence systems using a quality model. Applicable across all organizations developing and using AI. Establishes framework for assessing AI system quality.

novelty_note:
  AI quality evaluation is emerging; this standardizes approaches but follows established quality frameworks


draft_name: iso-18497-1-2024
overlap_note: Part of comprehensive ISO 18497 series; overlaps with Parts 2-4 on related safety principles
momentum_note: Published in 2024 as part of coordinated standards development for autonomous agricultural systems
relevance_note: Relevant for autonomous agricultural machinery development and safety-critical systems
categories: ["AI safety/alignment", "Policy/governance", "Human-agent interaction", "Autonomous netops"]
rated_at: 2026-03-08T17:14:26.881314+00:00
summary:
  Specifies design principles for agricultural machinery with partially automated, semi-autonomous and autonomous functions. Provides guidance on manufacturer information for safe working practices and residual risk management.

novelty_note:
  Extends existing safety standards to autonomous agricultural equipment; incremental advancement in domain-specific autonomy

maturity_note:
  Published standard addressing established agricultural machinery safety with new autonomous function considerations


draft_name: iso-18497-2-2024
maturity_note: Published standard with mature safety engineering principles applied to obstacle detection systems
overlap_note: Heavy overlap with ISO 18497-1 as Part 2 of series; closely related to Parts 3 and 4
momentum_note: Timely 2024 publication reflecting industry need for autonomous agricultural equipment safety
relevance_note: Relevant for developers of autonomous agricultural systems requiring obstacle detection
categories: ["AI safety/alignment", "Autonomous netops", "Policy/governance"]
rated_at: 2026-03-08T17:14:26.891283+00:00
summary:
  Specifies design principles for obstacle protection systems in autonomous agricultural machinery. Addresses safe working practices and residual risk communication from manufacturers.

novelty_note:
  Narrow focus on protective systems for autonomous equipment; incremental specialization within safety domain


draft_name: iso-18497-3-2024
maturity_note: Published standard applying established control system principles to autonomous zone management
overlap_note: Part 3 of ISO 18497 series with substantial overlap to Parts 1, 2, and 4
momentum_note: Current publication (2024) addressing specific autonomous operating constraint requirement
relevance_note: Relevant for autonomous systems requiring spatial constraint enforcement and zone management
categories: ["Autonomous netops", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:14:26.900502+00:00
summary:
  Specifies design principles for systems preventing autonomous agricultural machinery from exceeding operating zone boundaries. Covers perception and supervisory systems for boundary management.

novelty_note:
  Addresses geofencing and boundary enforcement in autonomous equipment; specialized safety mechanism for autonomy


draft_name: iso-18497-4-2024
maturity_note: Published standard with mature testing principles applied to autonomous systems verification
overlap_note: Part 4 of ISO 18497 series; directly referenced by and overlaps significantly with Parts 1-3
momentum_note: Recent 2024 publication completing comprehensive autonomous agricultural machinery safety standard
relevance_note: Highly relevant for safety-critical autonomous system development and validation methodologies
categories: ["AI safety/alignment", "Autonomous netops", "Policy/governance"]
rated_at: 2026-03-08T17:14:26.910171+00:00
summary:
  Specifies verification methods and validation principles for autonomous agricultural machinery. Addresses testing and validation of partially automated, semi-autonomous and autonomous functions.

novelty_note:
  Establishes verification/validation frameworks for autonomous equipment; important methodological contribution to safety assurance


draft_name: iso-pwi-18497-5
maturity_note: Early stage PWI (Preliminary Work Item); abstract lacks detail on specific technical content
momentum_note: Limited visibility into development momentum; part of multi-part series suggests sustained effort
categories: ["Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:14:39.307081+00:00
summary:
  Developing ISO standard for safety of partially automated, semi-autonomous and autonomous agricultural machinery and tractors. Part 5 covers open aspects of safety requirements for these systems.

novelty_note:
  Incremental work within established agricultural machinery safety framework; addresses known domain hazards

overlap_note:
  Overlaps with other autonomous system safety standards (ISO 26262, ISO 25119); domain-specific focus differentiates it

relevance_note:
  Relevant to agricultural automation sector; limited broader applicability to general autonomous systems


draft_name: iso-iec-15938-18-2023
maturity_note: Published standard (2023); mature with defined conformance procedures and reference implementations
momentum_note: Published status indicates established adoption pathway; multimedia compression is mature domain
categories: ["Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:14:39.318315+00:00
summary:
  ISO/IEC standard specifying conformance testing procedures and reference software for neural network compression implementations. Provides conformance bitstreams for compression testing.

novelty_note:
  Implementation specification for existing compression standard (15938-17); focuses on conformance rather than novel compression techniques

overlap_note:
  Part of broader MPEG-7 multimedia content description family; heavy overlap with related compression standards

relevance_note:
  Relevant to ML model serving/inference optimization; narrow focus on neural network compression testing


draft_name: iso-iec-pwi-7699
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:14:39.328301+00:00
summary:
  Developing ISO/IEC guidance standard for addressing security threats and failures in artificial intelligence systems. Covers threat identification and mitigation approaches.

novelty_note:
  Emerging AI safety standard addressing growing concerns; builds on general cybersecurity frameworks applied to AI context

maturity_note:
  Early stage PWI with minimal detail available; guidance nature suggests foundational rather than prescriptive content

overlap_note:
  Overlaps with ISO/IEC 27035 incident management and evolving AI safety standards; complements rather than duplicates

momentum_note:
  Strong momentum in AI security governance; reflects industry and regulatory focus on AI risk management

relevance_note:
  Highly relevant to AI safety/alignment and broader autonomous systems governance; wide applicability


draft_name: iso-13141-2024
categories: ["A2A protocols", "Data formats/interop", "Autonomous netops"]
rated_at: 2026-03-08T17:14:39.338334+00:00
summary:
  Published standard specifying localization augmentation communication for autonomous electronic fee collection systems. Defines short-range DSRC communication for OBE-RSE location sharing and identification.

novelty_note:
  Incremental extension of existing EFC standards (ISO 17573) to autonomous mode; applies known DSRC protocols to autonomous context

maturity_note:
  Published standard (2024) with detailed technical specifications for communication attributes and functions

overlap_note:
  Heavy overlap with ISO 12813, ISO 17573, and DSRC standards; tightly integrated into existing EFC ecosystem

momentum_note:
  Concurrent publication with related autonomous EFC standards indicates coordinated development; moderate adoption expected

relevance_note:
  Narrow relevance to toll collection systems; limited applicability beyond electronic fee collection domain


draft_name: iso-12813-2024
momentum_note: Published alongside ISO 13141 suggests coordinated autonomous EFC standardization effort
categories: ["A2A protocols", "Agent identity/auth", "Data formats/interop"]
rated_at: 2026-03-08T17:14:39.348197+00:00
summary:
  Published standard specifying compliance checking communication for autonomous electronic fee collection systems. Enables interrogation of on-board equipment to verify toll compliance without modifying OBE data.

novelty_note:
  Domain-specific extension of EFC standards to autonomous systems; uses established read-only interrogation model

maturity_note:
  Published standard (2024) with comprehensive technical specifications for compliance checking protocols

overlap_note:
  Heavy overlap with ISO 13141, ISO 17573, and related EFC standards; complementary rather than redundant

relevance_note:
  Specific to toll system compliance verification; minimal relevance outside electronic fee collection domain


draft_name: iso-iec-8183-2023
maturity_note: Published standard (2023) with complete specification and implementation guidance.
momentum_note: Published ISO standard indicates strong organizational adoption momentum in data governance.
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:51.027634+00:00
summary:
  Defines stages and actions for data processing throughout AI system life cycles, from acquisition through decommissioning. Applicable to all organizations using data in AI development and deployment.

novelty_note:
  Moderately novel framework for data governance in AI systems; addresses a recognized gap in lifecycle management standards.

overlap_note:
  Unique focus on data lifecycle; minimal overlap with other AI standards but complements governance frameworks.

relevance_note:
  Highly relevant for AI practitioners managing data throughout system lifecycles; applicable across industries.


draft_name: iso-iec-ts-8200-2024
categories: ["AI safety/alignment", "Autonomous netops", "Human-agent interaction", "Other AI/agent"]
rated_at: 2026-03-08T17:14:51.037103+00:00
summary:
  Technical specification for controllability frameworks in automated AI systems, covering state observability, control transfer, and uncertainty handling. Provides principles and approaches for enhancing AI system controllability.

novelty_note:
  Novel contribution to AI controllability domain; addresses critical safety and operational control concerns increasingly important for autonomous systems.

maturity_note:
  Published technical specification (2024) indicating mature standardization effort with practical implementation focus.

overlap_note:
  Specialized focus on controllability mechanisms; limited overlap with data lifecycle or general trustworthiness standards.

momentum_note:
  Recent 2024 publication suggests active development and growing recognition of controllability as critical standard area.

relevance_note:
  Essential for developers of autonomous and safety-critical AI systems; directly addresses human oversight and control requirements.


draft_name: iso-np-15801
maturity_note: Early-stage proposal (NP designation) with no publication date; minimal development maturity.
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:51.048656+00:00
summary:
  Specifies implementation and operation of information management systems for storing electronically stored information (ESI) in trustworthy and reliable manner. Covers policies, procedures, technology, and audit requirements for maintaining ESI integrity over time.

novelty_note:
  Low novelty; adapts existing document management principles to electronic storage without AI-specific considerations.

overlap_note:
  Significant overlap with general trustworthiness frameworks; related to but broader than AI-specific standards.

momentum_note:
  No publication date indicates stalled or early-stage development; limited momentum in standardization process.

relevance_note:
  Relevant for organizations managing archived ESI but lacks AI-system specificity; indirect relevance to AI governance.


draft_name: iso-pas-8800-2024
categories: ["AI safety/alignment", "Autonomous netops", "Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:14:51.059063+00:00
summary:
  Addresses safety-related E/E systems using AI technology in series-production road vehicles, covering undesired safety behavior from output insufficiencies and systematic errors. Includes internal and external AI element interactions affecting vehicle safety.

novelty_note:
  Novel and timely contribution addressing safety implications of AI in automotive; fills critical gap as vehicles increasingly integrate AI technologies.

maturity_note:
  Published PAS (2024) indicates formal standardization with practical automotive safety focus; industry-ready specification.

overlap_note:
  Highly specialized domain (automotive AI safety); minimal overlap with other standards except general AI governance principles.

momentum_note:
  Recent publication (Dec 2024) and automotive industry demand for AI safety standards indicate strong momentum.

relevance_note:
  Critical for automotive manufacturers and suppliers integrating AI into safety-critical vehicle systems; high practical relevance.


draft_name: iso-iec-pwi-9991
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:14:51.067816+00:00
summary:
  Provides overview and concepts for trustworthiness in information technology. Establishes foundational vocabulary and conceptual framework for trustworthiness standards development.

novelty_note:
  Moderate novelty as foundational framework; useful for standardization but covers established trustworthiness concepts.

maturity_note:
  Pre-work item (PWI) status indicates early conceptual stage with no publication timeline; minimal maturity.

overlap_note:
  Heavy overlap with existing trustworthiness frameworks and standards; foundational but not differentiated.

momentum_note:
  PWI status with no date suggests limited development progress and uncertain commitment to completion.

relevance_note:
  Relevant as conceptual foundation for trustworthiness standards but lacks concrete AI-system implementation guidance.


draft_name: iso-iec-cd-11034.2
maturity_note: Committee draft stage indicates early-to-mid maturity; foundational concepts not yet finalized
momentum_note: No publication date provided; unclear advancement status or adoption trajectory
relevance_note: Relevant for cloud-based AI systems but not specifically focused on AI trustworthiness
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:15:02.245671+00:00
summary:
  Provides frameworks and concepts for trustworthiness in cloud computing systems. Covers overview and foundational principles for assessing trust in cloud environments. Applicable to cloud service providers and consumers.

novelty_note:
  Trustworthiness frameworks for cloud are well-established; this appears to be a consolidation rather than novel approach

overlap_note:
  Moderate overlap with cloud governance and policy frameworks; some connection to AI safety concerns in cloud contexts


draft_name: iso-dtr-12786
momentum_note: No publication date provided; unclear if this is an active or stalled initiative
relevance_note: Relevant primarily to intelligent transport systems; limited broader AI/agent framework relevance
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:15:02.256956+00:00
summary:
  Technical report on use cases for big data and artificial intelligence in intelligent transport systems. Focuses on practical applications of AI/big data within ITS domain. Provides examples and scenarios for ITS stakeholders.

novelty_note:
  Use case documentation is largely domain-specific; limited novel methodology or technical contribution beyond application examples

maturity_note:
  Draft technical report status suggests preliminary compilation; use cases may not be validated or widely tested

overlap_note:
  Minimal overlap with other drafts; highly specialized to ITS domain with limited cross-domain applicability


draft_name: iso-iec-ts-12791-2024
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:15:02.266140+00:00
summary:
  Addresses unwanted bias in machine learning systems performing classification and regression tasks. Provides mitigation techniques applicable throughout AI system lifecycle. Applicable to organizations of all sizes implementing ML-based AI systems.

novelty_note:
  Bias mitigation in ML is established practice; document appears to formalize and standardize existing techniques rather than introduce novel approaches

maturity_note:
  Published technical specification (2024) indicates reasonable maturity; builds on established ML practices with standardized approach

overlap_note:
  Overlaps with AI safety/alignment concerns and transparency requirements; complements but does not duplicate other governance standards

momentum_note:
  Recent publication (2024) with clear relevance to active AI governance discussions; likely to see adoption

relevance_note:
  Highly relevant to responsible AI development; directly addresses critical AI safety concern applicable across sectors


draft_name: iso-iec-12792-2025
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:15:02.274724+00:00
summary:
  Specifies taxonomy of information elements for AI system transparency. Assists stakeholders in identifying and addressing transparency needs. Applicable to any organization implementing AI systems.

novelty_note:
  AI transparency taxonomies are emerging; this standardization is useful but represents formalization of known requirements rather than novel concept

maturity_note:
  Forthcoming publication (2025) with structured taxonomy approach suggests solid specification maturity; ready for near-term adoption

overlap_note:
  Overlaps with AI safety, bias mitigation, and governance frameworks; complements rather than duplicates existing standards

momentum_note:
  Recent publication date (2025) aligns with current regulatory momentum around AI transparency and accountability

relevance_note:
  Highly relevant to AI governance and stakeholder trust; directly supports regulatory compliance and responsible AI practices


draft_name: iso-iec-ts-42119-2-2025
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:15:02.283732+00:00
summary:
  Provides requirements and guidance for applying ISO/IEC/IEEE 29119 testing series to AI systems. Uses risk-based approach to identify suitable testing practices for AI development. Specifies additional detail on test application in AI contexts.

novelty_note:
  Risk-based testing for AI is established practice; document primarily adapts existing software testing standards to AI domain rather than introducing novel testing paradigm

maturity_note:
  Technical specification status with recent publication date (2025) indicates good maturity; provides practical mapping of established standards

overlap_note:
  Minimal overlap; primarily technical specification distinct from governance/transparency/bias standards; fills specific testing guidance gap

momentum_note:
  Recent publication aligns with growing need for standardized AI testing practices; addresses recognized gap in AI quality assurance

relevance_note:
  Relevant to organizations developing and maintaining AI systems; supports quality assurance and risk management objectives


draft_name: iso-iec-tr-24030-2024
novelty_note: Descriptive overview document with limited novel technical contribution
maturity_note: Published standard from 2024, represents mature consensus on AI use case categorization
overlap_note: Moderate overlap with general AI standards and domain-specific AI guidance documents
momentum_note: Standard publication indicates stable interest but limited forward momentum in this specific area
relevance_note: Useful reference for practitioners but addresses breadth over depth of technical implementation
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:15:13.715244+00:00
summary:
  Collection of representative AI application use cases across various domains. Provides illustrative examples of how AI is deployed in practice, serving as a reference for understanding AI implementation patterns.


draft_name: iso-iec-5259-5-2025
relevance_note: Highly relevant for organizations implementing ML systems requiring formal governance controls
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:15:13.724890+00:00
summary:
  Establishes governance framework for data quality in analytics and ML systems throughout the data lifecycle. Provides organizational controls and oversight structures for managing data quality implementation.

novelty_note:
  Applies existing governance concepts to ML-specific data quality context; moderate novelty in governance structure design

maturity_note:
  Recently published in 2025, part of coordinated ISO/IEC 5259 series indicating high maturity and standardization

overlap_note:
  Limited overlap; specialized governance framework addresses specific gap in data quality management standards

momentum_note:
  Recent publication and multi-part series structure indicates strong ongoing standardization momentum


draft_name: iso-22733-1-2022
maturity_note: Published in 2022, represents mature testing standard for automotive safety systems
overlap_note: Unique to vehicle safety domain; minimal overlap with general AI/agent standards
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:15:13.733799+00:00
summary:
  Specifies evaluation methods for autonomous emergency braking systems in vehicle-to-vehicle collision scenarios. Focuses on testing protocols for longitudinal accident mitigation performance.

novelty_note:
  Applies established testing methodology to autonomous vehicle safety; incremental advancement in specific domain

momentum_note:
  Domain-specific standard with limited cross-domain momentum or relevance to broader AI standardization

relevance_note:
  Limited relevance to general AI agent standards; highly specialized to automotive collision avoidance


draft_name: iso-np-4669-3
overlap_note: Some conceptual overlap with agent authentication and source verification concerns
momentum_note: Early development stage with unclear momentum or adoption trajectory
categories: ["Agent identity/auth", "Policy/governance"]
rated_at: 2026-03-08T17:15:13.742595+00:00
summary:
  Specifies requirements and procedures for assessing trustworthiness of documents received from third parties. Addresses document validation and trust evaluation in information management contexts.

novelty_note:
  Applies document management principles to trustworthiness assessment; limited novelty for AI-specific applications

maturity_note:
  Early stage NP (New Project) with no publication date; pre-standardization phase with minimal maturity

relevance_note:
  Tangentially relevant to AI agent identity and trust, but primarily document-focused rather than agent-focused


draft_name: iso-iec-23093-5-2025
momentum_note: Recent publication in established series indicates ongoing active standardization of IoMT domain
categories: ["Data formats/interop", "A2A protocols", "Autonomous netops"]
rated_at: 2026-03-08T17:15:13.751909+00:00
summary:
  Specifies data formats and APIs for mission management and control in Internet of Media Things networks. Defines XML-based structured formats for mission assignment and user command protocols.

novelty_note:
  Develops specialized data format specifications for IoMT autonomous collaboration; moderate technical novelty in media-specific protocols

maturity_note:
  Published in 2025 as part of ISO/IEC 23093 series; demonstrates mature standardization of IoMT specifications

overlap_note:
  Limited overlap; specialized to media-focused IoT with distinct protocol requirements from general agent standards

relevance_note:
  Relevant for media-specific autonomous systems and IoT agent coordination, moderate general applicability


draft_name: iso-iec-dts-42119-3.2
maturity_note: DTS (Draft Technical Specification) stage; well-developed guidance based on ISO/IEC 22989 framework
overlap_note: Overlaps with general AI governance and testing standards; complements ISO 18374 on data aspects
momentum_note: Active development through ISO/IEC JTC 1/SC 42; addresses critical industry need for V&V standards
relevance_note: Highly relevant to AI system deployment safety and quality assurance across all sectors
categories: ["Policy/governance", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:15:25.911721+00:00
summary:
  Provides guidance on verification and validation processes for AI systems throughout their lifecycle, covering formal methods, simulation, and evaluation approaches. Applicable across organizations developing, deploying, or using AI systems.

novelty_note:
  Standard verification/validation framework; addresses established practices rather than novel approaches


draft_name: iso-iec-pwi-17866
novelty_note: General ethical guidance framework; covers well-established responsible AI principles
maturity_note: PWI (Proposed Work Item) stage; early development with minimal concrete deliverables documented
momentum_note: Early-stage proposal; limited visibility into development progress or adoption trajectory
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:15:25.922325+00:00
summary:
  Provides best practice guidance for organizations to mitigate ethical and societal concerns arising from AI deployment. Addresses responsible AI implementation across organizational contexts.

overlap_note:
  Significant overlap with broader AI governance and ethics standards in development; complements DTS 42119-3.2

relevance_note:
  Important for responsible AI governance but addresses established concerns rather than novel challenges


draft_name: iso-iec-tr-17903-2024
maturity_note: Published TR (Technical Report) as of 2024; mature informational document with current examples
overlap_note: Limited overlap; focuses on hardware/device layer distinct from higher-level AI system concerns
momentum_note: Recently published; establishes reference baseline but no indication of active extension work
categories: ["Model serving/inference", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:15:25.931347+00:00
summary:
  Technical report surveying machine learning computing devices, including terminology, characteristics, and approaches for optimizing device performance. Relevant to organizations of all sizes implementing ML systems.

novelty_note:
  Comprehensive survey of existing ML device landscape; documents current practices rather than innovations

relevance_note:
  Relevant for ML infrastructure but limited applicability to AI governance, safety, or ethical concerns


draft_name: iso-iec-awi-31310-1
momentum_note: Active work item with multi-part structure indicating sustained development effort
relevance_note: Relevant for establishing coherent trustworthiness frameworks across AI and broader IT systems
categories: ["Data formats/interop", "Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:15:25.941321+00:00
summary:
  Describes ontology framework and foundational concepts for trustworthiness in information technology systems. Establishes taxonomies and definitions for trustworthiness attributes and relationships.

novelty_note:
  Novel ontological formalization of trustworthiness; provides structured framework for cross-domain application

maturity_note:
  AWI (Approved Work Item) stage; foundational framework in development; Part 1 of multi-part standard

overlap_note:
  Foundational layer supporting other AI standards; complements but distinct from application-specific guidance


draft_name: iso-18374-2025
momentum_note: Recently published; indicates active standardization effort for regulated medical AI applications
relevance_note: Highly relevant for dental AI deployment; limited relevance to broader AI governance frameworks
categories: ["Policy/governance", "Data formats/interop", "AI safety/alignment"]
rated_at: 2026-03-08T17:15:25.951584+00:00
summary:
  Defines requirements for developing AI/augmented intelligence systems for dental 2D radiograph analysis, covering data generation, annotation, and processing standards. Ensures systems achieve intended goals with appropriate training and validation data.

novelty_note:
  Domain-specific application of AI/AuI standards to dentistry; novel in sector-specific adaptation but follows established AI development patterns

maturity_note:
  Published standard as of 2025; mature, sector-specific guidance with clear implementation requirements

overlap_note:
  Domain-specific application with limited overlap; complements DTS 42119-3.2 with dental-specific instantiation


draft_name: iso-awi-18460
momentum_note: Niche application area; limited momentum in broader AI/agent standards landscape
relevance_note: Low relevance to general AI agent systems; specific to lawn equipment autonomous functions
categories: ["Other AI/agent"]
rated_at: 2026-03-08T17:15:36.857434+00:00
summary:
  Safety standard for autonomous combustion-engine-powered lawnmowers with metallic or non-metallic cutting means. Specifies hazard verification and safety requirements for intended use and foreseeable misuse.

novelty_note:
  Domain-specific safety standard with limited novelty to general AI/agent systems; focuses on mechanical hazards rather than AI oversight

maturity_note:
  Published standard in mature development stage; Type C standard indicates established safety framework

overlap_note:
  Minimal overlap with AI system standards; addresses physical equipment safety rather than AI governance


draft_name: iso-iec-pwi-18966
momentum_note: Strong momentum as proactive governance standard addressing urgent AI oversight needs
categories: ["AI safety/alignment", "Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:15:36.869017+00:00
summary:
  Proposed standard for oversight mechanisms of AI systems. Addresses governance and control frameworks for AI system deployment and monitoring.

novelty_note:
  High novelty as early-stage standard addressing critical AI governance gap; PWI stage indicates emerging work

maturity_note:
  Very early stage (PWI - Preliminary Work Item); minimal content available; substantial development required

overlap_note:
  Potentially overlaps with health informatics AI (18988) and could relate to supervised agent architectures

relevance_note:
  Highly relevant to AI agent systems governance and safety; addresses fundamental oversight requirements


draft_name: iso-iec-15938-17-2024
overlap_note: Related to model serving and data formats; some overlap with neural network interchange standards
categories: ["Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:15:36.878223+00:00
summary:
  Specifies neural network compression techniques for multimedia content analysis. Defines compression methods, quantization, entropy coding, and integration with existing exchange formats.

novelty_note:
  Moderate novelty; compression of neural networks is established area but standardization of codec adds value

maturity_note:
  Published 2024 standard; mature specification with complete technical details and decoding requirements

momentum_note:
  Steady momentum in multimedia and neural network standardization; incremental progress on compression

relevance_note:
  Relevant to model serving/inference efficiency but limited direct relevance to agent systems and oversight


draft_name: iso-cd-tr-22957
novelty_note: Established domain with incremental updates; content management best practices are well-documented
maturity_note: Technical report status indicates mature guidance; likely builds on established ISO standards
overlap_note: Minimal overlap with AI/agent-focused standards; distinct from modern data governance concerns
momentum_note: Document management is stable field; limited momentum toward new paradigms
relevance_note: Low relevance to autonomous systems, AI agents, or distributed intelligence networks
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:15:48.325480+00:00
summary:
  Guidelines for organizations implementing enterprise content management (ECM) and electronically stored information (ESI) systems. Covers planning, design, and implementation across business analysis, vendor selection, and technology deployment. Addresses both in-house and outsourced/cloud solutions with multi-disciplinary stakeholder involvement.


draft_name: iso-iec-tr-20226-2025
overlap_note: Unique focus on environmental sustainability of AI systems; no heavy overlap with other standards
momentum_note: Strong momentum driven by ESG requirements and regulatory pressure on AI environmental impact
relevance_note: Relevant to AI/agent systems but focused on environmental rather than operational aspects
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:15:48.335113+00:00
summary:
  Overview of environmental sustainability aspects of AI systems throughout their lifecycle, including workload optimization, resource utilization, carbon impact, and pollution. Provides potential metrics for assessment but explicitly excludes how AI improves sustainability outcomes.

novelty_note:
  Emerging domain addressing growing concern about AI's environmental footprint; relatively novel focus area

maturity_note:
  Technical report status and recent 2025 publication suggest early-stage standardization; metrics still developing


draft_name: iso-20682-2026
novelty_note: Specialized domain for underwater robotics; moderate novelty in formal risk/reliability frameworks
momentum_note: Niche domain with steady but not accelerating interest; specialized application area
categories: ["Autonomous netops", "AI safety/alignment"]
rated_at: 2026-03-08T17:15:48.345065+00:00
summary:
  Specifies risk and reliability requirements for autonomous underwater vehicles (AUVs) in underwater environments. Covers sensors, communication devices, and mission-critical components while excluding AUGs, batteries, and electrical motors.

maturity_note:
  Upcoming 2026 publication suggests near-final standardization; builds on established AUV operational knowledge

overlap_note:
  Highly specialized to underwater vehicles; minimal overlap with other standards outside marine robotics

relevance_note:
  Limited relevance to general AI agents or smart systems; specific to underwater autonomous platforms


draft_name: iso-iec-pwi-20822
overlap_note: Some overlap with AI trustworthiness and data quality standards; smart cities context is specific
momentum_note: Smart cities momentum is strong; trustworthiness concerns increasingly critical for urban systems
relevance_note: Relevant to AI agents in distributed urban environments and knowledge-based decision-making
categories: ["AI safety/alignment", "Policy/governance", "Agent identity/auth"]
rated_at: 2026-03-08T17:15:48.355250+00:00
summary:
  Standard addressing domain knowledge trustworthiness evaluation for smart cities. Focus on assessing reliability and credibility of knowledge used in urban intelligence systems.

novelty_note:
  Smart cities domain is evolving; trustworthiness evaluation for domain knowledge is gaining emphasis

maturity_note:
  PWI (Preliminary Work Item) status indicates early-stage development; abstract minimal, unclear maturity


draft_name: iso-iec-tr-5259-6
overlap_note: Moderate overlap with other ISO/IEC 5259 parts and general data governance standards
momentum_note: Data quality concerns rising with ML adoption; visualization component adds practical value
relevance_note: Relevant to ML systems and agent training data quality; important for AI reliability
categories: ["Data formats/interop", "AI safety/alignment", "Model serving/inference"]
rated_at: 2026-03-08T17:15:48.363727+00:00
summary:
  Part 6 of data quality series addressing visualization frameworks for assessing data quality in analytics and machine learning systems. Provides tools for understanding and communicating data fitness for ML applications.

novelty_note:
  Data quality visualization is emerging specialization; part of broader ISO/IEC 5259 series on ML data quality

maturity_note:
  Technical report in multi-part series suggests developing standardization; visualization frameworks still maturing


draft_name: iso-iec-tr-21221-2025
maturity_note: Published standard (2025) with clear scope and use cases; mature framing of benefits framework
overlap_note: Minimal overlap; unique focus on benefit articulation rather than technical architecture or methods
momentum_note: Published TR suggests stable topic; benefits focus is growing area but not cutting-edge
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:15:59.235435+00:00
summary:
  Describes how AI systems deliver functional, economic, environmental, social, and cultural benefits to stakeholders. Includes illustrative use cases demonstrating beneficial AI outcomes across multiple dimensions.

novelty_note:
  Focuses on benefit delivery rather than technical mechanisms; adds stakeholder perception lens to AI system evaluation

relevance_note:
  Highly relevant for stakeholder communication and responsible AI framing; supports governance discussions


draft_name: iso-iec-ts-23220-6-2025
overlap_note: Specialized domain (eID/mobile identity); limited overlap with AI-focused standards
momentum_note: Published in 2025; incremental enhancement to established mobile identity ecosystem
relevance_note: Relevant for identity/authentication in agent systems; supports secure agent identity verification
categories: ["Agent identity/auth", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:15:59.245897+00:00
summary:
  Specifies certification mechanisms for trustworthiness of secure areas in mobile identity management systems. Defines capabilities descriptors and certificate structures for eID providers and attestation services.

novelty_note:
  Extends existing mobile identity framework; adds trustworthiness certification layer specific to secure area providers

maturity_note:
  Published TS (2025) with specific technical requirements; builds on established ISO/IEC 23220-1 foundation


draft_name: iso-iec-cd-42102
maturity_note: Committee Draft stage indicates early development; framework not yet finalized
relevance_note: Highly relevant for interoperability and common understanding across AI agent ecosystems
categories: ["Data formats/interop", "Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:15:59.256417+00:00
summary:
  Provides a framework of descriptors for characterizing AI system methods and capabilities consistently. Enables stakeholders to describe and achieve common understanding of AI systems across lifecycle stages.

novelty_note:
  Develops comprehensive characterization vocabulary for AI systems; addresses communication gap across stakeholder roles

overlap_note:
  Moderate overlap with other AI characterization/assessment standards; complements but distinct from robustness/synthetic data specs

momentum_note:
  CD status suggests active development with institutional backing; characterization frameworks gaining traction


draft_name: iso-iec-cd-tr-42103
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:15:59.265013+00:00
summary:
  Provides overview of synthetic data concepts, methods, uses, and considerations in AI system contexts. Covers generation approaches and application scenarios for synthetic data in AI.

novelty_note:
  Synthesizes synthetic data landscape for AI; addresses emerging practice area with growing importance

maturity_note:
  Committee Draft TR indicates exploratory stage; foundational overview rather than prescriptive guidance

overlap_note:
  Unique focus on synthetic data in AI; minimal overlap with other drafts though relevant to training considerations

momentum_note:
  Synthetic data is high-momentum area; CD status with TR designation shows strong interest and active development

relevance_note:
  Relevant for training data management, bias mitigation, and privacy-preserving AI system development


draft_name: iso-iec-dis-24029-3
maturity_note: DIS stage indicates draft for public comment; methodology not yet formally approved
relevance_note: Relevant for AI safety, validation, and regulatory compliance of neural network-based agent systems
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:15:59.273932+00:00
summary:
  Provides methodology for applying statistical methods to assess robustness properties of neural networks. Guides selection, application, and management of statistical techniques for robustness evaluation.

novelty_note:
  Focuses on practical statistical methodologies for robustness assessment; methodologically detailed guidance for testing neural networks

overlap_note:
  Specific to robustness assessment of neural networks; complements but distinct from general AI characterization

momentum_note:
  Robustness assessment gaining regulatory importance; DIS status indicates progression toward standard


draft_name: iso-iec-dis-42105
novelty_note: Human oversight is established practice; guidance documents are incremental to existing frameworks
maturity_note: DIS stage indicates advanced development; builds on mature precedent standards
overlap_note: Overlaps with 22443 on governance/management; aligns with general AI system lifecycle standards
momentum_note: Active development stage suggests strong organizational commitment to standardization
relevance_note: Highly relevant for critical AI deployments requiring human-in-the-loop verification
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:16:10.151647+00:00
summary:
  Provides guidance on human oversight and monitoring of AI systems throughout their lifecycle. Extends ISO/IEC TS 8200 with practical requirements for human control mechanisms. Applicable across all organization types.


draft_name: iso-iec-tr-42106
novelty_note: Benchmarking is well-established; this is primarily a survey/overview of existing approaches
maturity_note: TR designation indicates preliminary/informational content rather than normative requirements
overlap_note: Unique focus on benchmarking methodology; limited overlap with other governance/safety documents
momentum_note: Early-stage TR suggests emerging consensus on benchmarking differentiation needs
relevance_note: Relevant for organizations evaluating and comparing AI system quality assurance
categories: ["Model serving/inference", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:16:10.161023+00:00
summary:
  Overview document for differentiated benchmarking approaches to evaluate AI system quality characteristics. Technical report focused on assessment methodologies. Supports comparative evaluation across varying AI system types.


draft_name: iso-fdis-15801
momentum_note: Advanced stage indicates strong support; likely to become published standard soon
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:16:10.169984+00:00
summary:
  Specifies requirements for trustworthy and reliable management of electronically stored information over time. Covers system implementation, audit, and policies for maintaining ESI integrity. Applicable to any organization storing digital records.

novelty_note:
  Document archival and trustworthiness are mature domains; FDIS stage represents consolidation of existing practice

maturity_note:
  FDIS (Final Draft International Standard) indicates near-complete standardization; ready for publication

overlap_note:
  Tangentially related to AI governance but primarily focuses on general information management; heavy overlap with existing records management standards

relevance_note:
  Limited direct relevance to AI systems; primarily applicable to digital record preservation infrastructure


draft_name: iso-iec-wd-ts-22440
momentum_note: Active working draft development suggests commitment; functional safety in AI is priority area
categories: ["AI safety/alignment", "Autonomous netops", "Policy/governance"]
rated_at: 2026-03-08T17:16:10.178807+00:00
summary:
  Provides requirements and guidance for functional safety in AI systems, covering ML safety, security threats affecting safety, and use of AI in safety-critical functions. Addresses design, development, and verification of safety-related AI components.

novelty_note:
  Combines established safety engineering with emerging AI/ML concerns; moderately novel intersection of two mature domains

maturity_note:
  WD (Working Draft) stage indicates early-stage development; substantial work remains before standardization

overlap_note:
  Overlaps with 42105 on AI governance and 22443 on ethical concerns; complements but distinct from each

relevance_note:
  Highly relevant for safety-critical AI deployments in autonomous systems, medical devices, industrial control


draft_name: iso-iec-cd-ts-22443
momentum_note: Committee-level development suggests broad stakeholder engagement and commitment
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:16:10.187739+00:00
summary:
  Guidance on identifying and addressing societal concerns and ethical considerations in AI systems throughout lifecycle. Expands governance and impact assessment frameworks. Addresses potential harms to individuals and society.

novelty_note:
  AI ethics and governance are emerging; guidance is somewhat novel but builds on established CSR/impact assessment practices

maturity_note:
  CD (Committee Draft) stage indicates mid-stage development; significant revision likely before publication

overlap_note:
  Overlaps with 42105 on human oversight and 22440 on safety; distinct focus on broader ethical/societal impacts

relevance_note:
  Increasingly relevant as organizations face regulatory and stakeholder pressure on AI ethics and governance


draft_name: iso-iec-cd-23282
categories: ["Policy/governance", "Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:16:24.679124+00:00
summary:
  Specifies evaluation methods for natural language processing systems, including quantitative metrics and guidance on implementation and interpretation. Covers requirements for technical resources involved in NLP system assessment and functional suitability measurement.

novelty_note:
  Standard evaluation frameworks for NLP are established; this contribution adds structured ISO guidance but represents incremental formalization rather than novel methodology.

maturity_note:
  Committee draft stage indicates mature conceptualization; ready for standardization but still undergoing refinement before final publication.

overlap_note:
  Minimal overlap with other drafts; specialized focus on NLP evaluation metrics distinguishes it from broader AI governance or trust frameworks.

momentum_note:
  Limited evidence of industry adoption momentum; standardization process is ongoing but lacks clear momentum indicators in abstract.

relevance_note:
  Moderately relevant to AI system quality assurance; important for NLP deployment but narrow scope limits broader applicability to agent systems.


draft_name: iso-16363-2025
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:16:24.689114+00:00
summary:
  Defines CCSDS Recommended Practice for auditing and certifying trustworthy digital repositories across all repository types. Establishes baseline standards for assessing repository trustworthiness.

novelty_note:
  Digital repository audit frameworks are well-established; this 2025 update formalizes existing CCSDS practices into ISO standard with limited conceptual novelty.

maturity_note:
  Published standard (2025) indicates high maturity; builds on established CCSDS recommendations demonstrating mature, operationalized approach.

overlap_note:
  Moderate overlap with ISO 16919 (complementary certification body requirements) and some overlap with data governance frameworks.

momentum_note:
  Recent publication date (March 2025) and CCSDS pedigree suggest moderate-to-good adoption momentum in space/archival communities.

relevance_note:
  Limited relevance to agent systems; primarily addresses static data repository trustworthiness rather than autonomous agent operations or intelligence.


draft_name: iso-16919-2025
categories: ["Policy/governance"]
rated_at: 2026-03-08T17:16:24.699376+00:00
summary:
  Defines requirements for organizations performing audit and certification of trustworthy digital repositories using ISO 16363 standards. Specifies operational requirements based on ISO/IEC 17021-1 conformity assessment metrics.

novelty_note:
  Conformity assessment body requirements follow established ISO/IEC 17021 framework; application to digital repositories represents standard adaptation rather than novel methodology.

maturity_note:
  Published standard (March 2025) with clear grounding in mature ISO/IEC 17021 framework indicates high operational maturity.

overlap_note:
  Heavy overlap with ISO 16363 (assessment object) and ISO/IEC 17021-1 (framework basis); strongly complementary rather than independent.

momentum_note:
  Recent publication and CCSDS foundation suggest solid adoption momentum in space/data management sectors.

relevance_note:
  Minimal relevance to agent systems; focuses on static repository audit bodies rather than dynamic autonomous agent trustworthiness or operations.


draft_name: iso-iec-dtr-23888-1
momentum_note: DTR status and missing page count suggest early-stage work with uncertain adoption trajectory.
categories: ["Model serving/inference", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:16:24.714196+00:00
summary:
  Provides vision and scenarios for artificial intelligence applied to multimedia systems under ISO/IEC JTC 1/SC 29 standardization effort. Establishes foundational concepts and use cases for AI-multimedia integration.

novelty_note:
  AI-multimedia integration is active research area; this visioning document establishes direction but lacks concrete technical specifications or novel architectural contributions.

maturity_note:
  Draft Technical Report (DTR) stage indicates early-stage conceptualization; preliminary framework still being developed before advancement to full standard.

overlap_note:
  Unique focus on multimedia-specific AI scenarios; minimal direct overlap with other drafts focused on NLP, repositories, or medical device ML.

relevance_note:
  Moderately relevant to multimodal AI agents; provides visioning for multimedia AI but lacks operational guidance for agent deployment.


draft_name: iso-dts-24971-2.2
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:16:24.726112+00:00
summary:
  Provides guidance on applying ISO 14971 risk management to machine learning-enabled medical devices. Addresses ML-specific risks including data management, bias, model training, evaluation, and continuous learning in medical contexts.

novelty_note:
  ML-specific medical device risk guidance is novel contribution; systematic treatment of ML risks (bias, retraining, data management) extends traditional risk frameworks into adaptive systems domain.

maturity_note:
  Draft Technical Specification (DTS) stage indicates developed but not-yet-finalized guidance; conceptually mature but pending standardization completion.

overlap_note:
  Unique medical device + ML focus; minimal overlap with other drafts except general AI governance considerations.

momentum_note:
  DTS status and regulatory medical device context suggest moderate momentum; regulatory drivers may accelerate adoption.

relevance_note:
  Highly relevant to autonomous agent safety; directly addresses adaptive systems risk management, continuous learning, and bias mitigation applicable to agents.


draft_name: iso-iec-15938-18-2025
maturity_note: Published standard (2025) with complete specifications and reference implementations.
overlap_note: Minimal overlap with other drafts; specialized compression-focused standard.
momentum_note: Published but narrow scope limits broader adoption momentum.
relevance_note: Relevant primarily to neural network model optimization and compression specialists.
categories: ["Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:16:34.611121+00:00
summary:
  Specifies conformance testing procedures and reference software for neural network compression implementations under ISO/IEC 15938-17. Provides bitstreams and validation methods for standardized compression techniques.

novelty_note:
  Narrow focus on compression conformance testing; limited novelty as it primarily operationalizes an existing standard.


draft_name: iso-dis-24051-1
maturity_note: Draft standard (DIS) still in development; not yet published.
momentum_note: Active development in healthcare AI regulation suggests sustained momentum.
relevance_note: Highly relevant to regulated medical AI deployment and clinical laboratory operations.
categories: ["Policy/governance", "AI safety/alignment", "Data formats/interop"]
rated_at: 2026-03-08T17:16:34.622431+00:00
summary:
  Establishes general principles for applying artificial intelligence methods in medical laboratory settings. Covers machine learning, deep learning, neural networks, expert systems, and image analysis.

novelty_note:
  Applies existing AI concepts to medical domain; some novelty in establishing medical lab-specific governance framework.

overlap_note:
  Moderate overlap with Part 2 on digital pathology; general principles layer above domain-specific implementations.


draft_name: iso-cd-24051-2
maturity_note: Committee Draft (CD) stage; early development with significant revisions likely.
overlap_note: High overlap with Part 1 on medical lab AI principles; Part 2 is domain-specific instantiation.
momentum_note: Digital pathology adoption accelerating; draft addresses emerging clinical need.
relevance_note: Directly applicable to pathology labs implementing AI-assisted diagnostics.
categories: ["Policy/governance", "AI safety/alignment", "Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:16:34.632793+00:00
summary:
  Specifies requirements for digitizing pathology slides, processing whole slide images, and applying AI-based image analysis to anatomical pathology. Covers workflow from slide preparation through automated analysis.

novelty_note:
  Operationalizes digital pathology workflows with AI; moderate novelty in establishing medical-specific image analysis standards.


draft_name: iso-22133-2026
maturity_note: Published standard (2026) with complete specifications.
overlap_note: Unique focus on test vehicle control protocols; minimal overlap with other drafts.
momentum_note: Strong momentum from autonomous vehicle industry demand for standardized testing.
relevance_note: Critical for autonomous vehicle development and safety validation.
categories: ["A2A protocols", "Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:16:34.642234+00:00
summary:
  Defines control protocols, message formats, and functional requirements for test object monitoring in autonomous vehicle and active safety testing. Enables multi-vendor interoperable test environments.

novelty_note:
  Novel in standardizing cross-vendor test object communication; primarily integrates existing testing concepts.


draft_name: iso-iec-22989-2022-damd-1
maturity_note: Amendment to published standard (2022 base); amendment status unclear but likely finalized.
overlap_note: Minimal overlap; primarily terminology and definitional work.
momentum_note: Generative AI prominence drives continued updates to foundational standards.
relevance_note: Relevant to standards developers and those implementing ISO AI terminology frameworks.
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:16:34.650984+00:00
summary:
  Amendment to AI concepts and terminology standard adding definitions and frameworks specific to generative AI. Extends terminology for emerging generative AI systems.

novelty_note:
  Incremental amendment; extends existing standard with generative AI concepts rather than establishing new principles.


draft_name: iso-iec-23053-2022-damd-1
maturity_note: Published standard amendment with full ISO/IEC approval and formal status
momentum_note: Published amendment indicates active standardization but limited ongoing development momentum
relevance_note: Highly relevant for AI system governance and standardized development practices across industries
categories: ["Policy/governance", "Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:16:45.892946+00:00
summary:
  Amendment to the Framework for AI Systems Using ML that specifically addresses generative AI capabilities and requirements. Extends existing ISO/IEC 23053:2022 with generative AI considerations for standardized AI system development.

novelty_note:
  Incremental amendment to existing standard rather than novel framework; generative AI specifics build on established ML foundations

overlap_note:
  Overlaps significantly with DIS 25059 and other SC 42 AI quality/framework standards; part of coordinated standards family


draft_name: iso-iec-dis-25059
momentum_note: DIS stage suggests active progression toward publication with substantial committee engagement
relevance_note: Critical for establishing measurable AI system quality requirements and evaluation criteria
categories: ["Policy/governance", "Data formats/interop", "Human-agent interaction"]
rated_at: 2026-03-08T17:16:45.903661+00:00
summary:
  Defines quality models and characteristics for evaluating AI systems and services as an extension to SQuaRE standards. Provides consistent terminology and metrics for specifying and measuring AI system quality.

novelty_note:
  Application-specific quality model for AI; builds on established SQuaRE framework with AI-specific adaptations

maturity_note:
  DIS (Draft International Standard) status indicates advanced development stage with formal review underway

overlap_note:
  Strong overlap with ISO/IEC 23053 on AI frameworks and quality aspects; complementary to human-machine teaming standard


draft_name: iso-iec-cd-tr-42109
categories: ["Human-agent interaction", "Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:16:45.914551+00:00
summary:
  Technical report documenting use cases and practical scenarios for human-machine teaming in AI systems. Provides real-world examples and guidance for implementing collaborative AI-human systems.

novelty_note:
  Use case collection represents practical knowledge synthesis rather than novel technical contribution; TR format indicates guidance rather than normative standard

maturity_note:
  CD (Committee Draft) status indicates early development stage; technical report format suggests lower formality than full standards

overlap_note:
  Moderate overlap with human-agent interaction aspects of other SC 42 standards; complements quality and framework standards

momentum_note:
  CD stage and TR designation suggest slower progression; may serve supporting rather than primary standardization role

relevance_note:
  Valuable for practitioners implementing human-AI collaboration; provides grounding for abstract standards


draft_name: iso-iec-np-ts-42110
categories: ["Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:16:45.926261+00:00
summary:
  Proposes comprehensive AI inference framework covering concepts, modeling, components, processes and performance for AI systems. Addresses generalized inference requirements across diverse AI system types.

novelty_note:
  Inference framework is established concept; contribution focuses on standardized terminology and comprehensive modeling rather than novel methodology

maturity_note:
  NP (New Proposal) status indicates earliest development stage with minimal formalization or committee consensus

overlap_note:
  Moderate overlap with model serving aspects in other standards; inference performance relates to SQuaRE quality models

momentum_note:
  NP status indicates very early stage with uncertain trajectory; limited evidence of substantial momentum

relevance_note:
  Relevant for standardizing AI inference practices and performance evaluation across deployment scenarios


draft_name: iso-iec-awi-ts-42111
categories: ["Model serving/inference", "Autonomous netops"]
rated_at: 2026-03-08T17:16:45.936168+00:00
summary:
  Provides guidance for developing and deploying lightweight AI systems designed for resource-constrained environments. Addresses optimization strategies for limited computational and memory resources.

novelty_note:
  Lightweight AI systems represent established practice; guidance document synthesizes known optimization approaches rather than introducing novel concepts

maturity_note:
  AWI (Approved Work Item) status indicates formal initiation but early development stage with minimal draft maturity

overlap_note:
  Minimal overlap with other standards; addresses specialized niche of resource-constrained deployment distinct from general AI frameworks

momentum_note:
  AWI status shows formal approval but uncertain development velocity; topic specificity may limit broad engagement

relevance_note:
  Moderately relevant for edge computing and IoT deployment scenarios; niche applicability compared to foundational standards


draft_name: iso-iec-dts-42112
overlap_note: Unique focus on training efficiency; minimal overlap with other drafts
momentum_note: Steady progress through DTS stage; practical applicability drives moderate adoption potential
relevance_note: Highly relevant for ML practitioners and AI system developers seeking efficiency improvements
categories: ["Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:17:01.748701+00:00
summary:
  Provides guidance on characteristics impacting ML model training efficiency and optimization approaches for AI providers and producers. Helps evaluate different training methodologies without specifying device-level acceleration mechanisms.

novelty_note:
  Moderately novel approach to systematizing training efficiency optimization; practical but incremental advancement

maturity_note:
  DTS (Draft Technical Specification) status indicates mature concept with good standardization readiness


draft_name: iso-iec-cd-31303.2
novelty_note: Low novelty; primarily definitional and organizational rather than introducing new concepts
maturity_note: CD (Committee Draft) stage suggests early development; foundational but not yet mature
relevance_note: Foundational relevance for establishing trustworthiness baseline across AI/IT domains
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:17:01.761616+00:00
summary:
  Overview document establishing trustworthiness concepts and definitions applicable to information technology systems. Provides foundational framework for IT trustworthiness standards.

overlap_note:
  High conceptual overlap with multiple AI safety/governance standards; trustworthiness is cross-cutting theme

momentum_note:
  Early stage development with broad applicability may slow convergence; foundational importance maintains slow momentum


draft_name: iso-iec-dis-24970
overlap_note: Specialized focus on AI logging; minimal direct overlap though complements other AI standards
relevance_note: Highly relevant for AI system governance, auditability, and risk management compliance
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:17:01.773211+00:00
summary:
  Specifies common capabilities, requirements, and information model for AI system event logging integrated with risk management frameworks. Standardizes logging practices across AI systems.

novelty_note:
  Moderately novel standardization of logging in AI context; builds on general IT logging with AI-specific requirements

maturity_note:
  DIS (Draft International Standard) stage indicates substantial development maturity and near-publication readiness

momentum_note:
  Advanced DIS stage with clear risk management integration demonstrates strong standardization momentum


draft_name: iso-pwi-24986
relevance_note: Relevant primarily for building energy management sector; limited cross-domain applicability
categories: ["Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:17:01.783993+00:00
summary:
  Comprehensive standard for determining energy performance of ML-based optimal control strategies in building systems through field measurement methods. Covers prediction models, optimization algorithms, and real-world deployment.

novelty_note:
  Moderately novel application of ML to building energy systems; combines domain-specific implementation with standard AI practices

maturity_note:
  PWI (Preliminary Work Item) stage indicates early conceptual phase with significant development ahead

overlap_note:
  Highly specialized domain focus on building energy; unique intersection of energy systems and ML optimization

momentum_note:
  Early PWI stage suggests emerging interest but limited momentum; niche application may slow adoption


draft_name: iso-iec-cd-25029
momentum_note: Moderate momentum as AI ethics attention grows; CD stage publication will drive awareness
categories: ["Human-agent interaction", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:01.794850+00:00
summary:
  Establishes definitions, concepts, and guidelines for AI-enhanced nudging mechanisms applied by organizations. Provides use-cases and requirements for responsible design aligned with existing AI standards.

novelty_note:
  High novelty addressing emerging concern of AI-enhanced behavioral influence; timely response to ethical AI challenges

maturity_note:
  CD stage indicates early development; concept maturity exists but standardization approach still evolving

overlap_note:
  Specialized focus on nudging mechanisms; limited overlap except with broader AI ethics/governance standards

relevance_note:
  Highly relevant for responsible AI governance and ethical deployment of behavioral influence systems


draft_name: iso-iec-ieee-np-29119-16
maturity_note: Mature standard development process (NP stage), builds on well-established testing methodologies
overlap_note: Minimal overlap with other drafts; focused niche on testing practices
momentum_note: Testing standards have steady adoption but ML-specific testing remains evolving area
relevance_note: High relevance for ML system quality assurance and risk management
categories: ["Policy/governance", "ML traffic mgmt", "AI safety/alignment"]
rated_at: 2026-03-08T17:17:12.192045+00:00
summary:
  Extends ISO/IEC/IEEE 29119 testing standards to machine learning systems, providing risk-based testing requirements and guidance. Covers test levels, practices, types, and design techniques specific to ML, excluding adaptive systems like reinforcement learning.

novelty_note:
  Applies existing testing frameworks to ML domain; moderately novel adaptation rather than fundamentally new approach


draft_name: iso-iec-cd-tr-23281
maturity_note: Early stage (CD) technical report; taxonomies remain subject to refinement
overlap_note: Unique focus on NLP task taxonomy; limited direct overlap with other drafts
momentum_note: Foundational work but NLP standards landscape is fragmented and rapidly changing
relevance_note: Relevant for interoperability and terminology standardization in NLP systems
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:17:12.202838+00:00
summary:
  Provides comprehensive overview and taxonomy of AI tasks and functionalities related to natural language processing. Maps existing and competing terminologies, task variants, language diversity impacts, and relationships with other standards.

novelty_note:
  Consolidates and organizes existing NLP tasks; primary value is in standardized landscaping and terminology rather than novel capabilities


draft_name: iso-iec-dis-23888-2
maturity_note: DIS stage indicates advancement but machine-oriented video coding is relatively nascent area
momentum_note: Growing importance as AI systems increasingly process video; momentum building in multimedia AI
relevance_note: Relevant for efficient ML inference on video data and computational optimization
categories: ["Data formats/interop", "Model serving/inference", "ML traffic mgmt"]
rated_at: 2026-03-08T17:17:12.212858+00:00
summary:
  Defines bitstream syntax, semantics, and decoding procedures for video encoded efficiently for machine analysis tasks. Specifies video coding optimized for machine performance rather than human perception.

novelty_note:
  Novel approach optimizing video coding for machine tasks rather than human viewing; represents emerging domain

overlap_note:
  Moderate overlap with Part 3 (optimization of encoders); both address machine analysis of coded video


draft_name: iso-dis-16400-6
maturity_note: DIS stage; integration of ML into automation systems is moderately established
overlap_note: Unique focus on equipment catalogues for virtual production; minimal overlap with other drafts
momentum_note: Niche application area with limited broader momentum in standards community
relevance_note: Relevant primarily for automation and virtual production domain specialists
categories: ["Data formats/interop", "Autonomous netops", "Other AI/agent"]
rated_at: 2026-03-08T17:17:12.222085+00:00
summary:
  Specifies equipment behaviour catalogues that incorporate machine learning models as components of equipment descriptions in virtual production systems. Enables ML-based representation of equipment behavior.

novelty_note:
  Applies ML models to equipment cataloguing; moderate novelty in integrating ML into existing automation standards


draft_name: iso-iec-dtr-23888-3.2
maturity_note: Early stage (DTR) technical report; machine-optimized video encoding optimization is immature area
relevance_note: Highly relevant for efficient ML-based video processing and computational resource optimization
categories: ["Data formats/interop", "Model serving/inference", "ML traffic mgmt"]
rated_at: 2026-03-08T17:17:12.233044+00:00
summary:
  Addresses optimization of video encoders and receiving systems for efficient machine analysis of coded video content. Complements Part 2 by focusing on encoder/decoder optimization for machine tasks.

novelty_note:
  Novel focus on end-to-end optimization of encoding systems for machine analysis; represents emerging specialization

overlap_note:
  Substantial overlap with Part 2 on machine analysis of video; both address video-machine optimization

momentum_note:
  Growing momentum as video AI inference becomes more prevalent; optimization focus increasingly relevant


draft_name: iso-19178-1-2025
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:17:25.879110+00:00
summary:
  Establishes a UML conceptual model for standardizing Earth Observation training data markup to improve interoperability across AI/ML tasks. Covers scene-level, object-level, and pixel-level supervised learning annotations with metadata specifications including identifiers, versions, and licensing.

novelty_note:
  Specialized domain (EO/EarthObservation) with novel structured approach to training data interoperability; fills gap in geospatial AI standardization

maturity_note:
  Published standard (2025) with mature conceptual model; implementable UML specification ready for adoption

overlap_note:
  Moderate overlap with ISO/IEC 22989-2 (AI terminology) and ISO/IEC CD 4213 (performance measurement); complements but distinct focus on data formats

momentum_note:
  Active publication timeline and domain-specific urgency in EO/geospatial AI; likely to see adoption in satellite imagery applications

relevance_note:
  Highly relevant to data interoperability challenges in distributed Earth Observation systems; supports broader AI standardization ecosystem


draft_name: iso-cd-25132
categories: ["Autonomous netops", "Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:17:25.889645+00:00
summary:
  Classifies civil unmanned aircraft system (UAS) autonomous flight control into 6 levels (0-5) based on human-machine role allocation. Provides standardized framework for evaluating autonomy in civil drone operations.

novelty_note:
  Adapts established autonomy level concepts (similar to SAE vehicle levels) to aviation domain; practical but not fundamentally novel methodology

maturity_note:
  Committee Draft stage indicates ongoing development; conceptual framework solid but implementation details likely still under refinement

overlap_note:
  Minimal overlap with other submissions; domain-specific aviation focus distinguishes it from broader AI standards

momentum_note:
  Growing regulatory interest in UAS autonomy but pre-standard maturity limits near-term momentum; depends on regulatory adoption timelines

relevance_note:
  Relevant for autonomous netops and safety-critical systems but narrow applicability; important for aviation but limited cross-domain utility


draft_name: iso-pwi-ts-21947
categories: ["Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:17:25.898664+00:00
summary:
  Technical specification providing guidelines for applying machine learning (supervised, unsupervised, reinforcement learning) to mass spectrometry data including spectra and imaging. Covers terminology, method selection, and data preparation procedures.

novelty_note:
  Domain-specific application guidance (mass spec) with limited novelty; synthesizes existing ML methods rather than introducing new frameworks

maturity_note:
  Preliminary Work Item stage indicates early-stage development; guidance-based approach less formalized than standards; acknowledges rapid method evolution

overlap_note:
  Significant overlap with ISO/IEC CD 4213 (performance measurement) and ISO/IEC AWI 22989-2 (terminology); largely complementary application domain

momentum_note:
  Pre-standard maturity and narrow analytical chemistry focus limit momentum; incremental contribution to domain-specific ML guidance

relevance_note:
  Limited relevance outside specialized analytical chemistry/materials science community; narrow technical scope reduces cross-domain applicability


draft_name: iso-iec-cd-4213
categories: ["Model serving/inference", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:17:25.908856+00:00
summary:
  Specifies methodologies for measuring AI model performance across classification, regression, clustering, and recommendation tasks. Establishes standardized metrics and evaluation frameworks for diverse AI applications.

novelty_note:
  Systematic compilation of performance measurement approaches; useful but incremental—most methods already established in ML literature

maturity_note:
  Committee Draft stage with foundational but not yet finalized specifications; good progress toward standardization of evaluation practices

overlap_note:
  Moderate overlap with ISO/IEC AWI 22989-2 (AI concepts) and ISO-19178-1 (training data interop); provides complementary evaluation layer

momentum_note:
  Clear practical need for performance measurement standardization; steady adoption likely but not urgent industry pressure

relevance_note:
  Broad relevance across all AI applications; fundamental utility for model validation and comparison in any AI ecosystem


draft_name: iso-iec-awi-22989-2
categories: ["Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:17:25.919594+00:00
summary:
  Establishes AI terminology and concepts specifically for healthcare applications. Supports standardized communication across diverse healthcare stakeholders and enables development of healthcare-specific AI standards.

novelty_note:
  Domain specialization of existing AI taxonomy (Part 1 general); necessary but incremental extension for healthcare sector alignment

maturity_note:
  Approved Work Item early stage; foundational terminology work is prerequisite for sector but incomplete relative to full standardization

overlap_note:
  Significant overlap with general ISO/IEC 22989 and moderate overlap with ISO-19178-1 and CD-4213; specialized vocabulary layer rather than new framework

momentum_note:
  Healthcare sector momentum for AI standards is growing but regulatory uncertainty limits near-term adoption pressure; long development timeline expected

relevance_note:
  Important for regulated healthcare AI but limited relevance outside medical domain; addresses critical terminology gap for clinical AI standards development


draft_name: iso-iec-awi-ts-25223
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:37.258120+00:00
summary:
  Provides guidance and requirements for quantifying uncertainties in AI systems across their entire lifecycle. Defines terminology and characteristics of uncertainty quantification approaches with practical applications.

novelty_note:
  Addresses important gap in AI system reliability by formalizing uncertainty quantification methods, which is relatively nascent in standards.

maturity_note:
  At AWI (Advanced Work Item) stage, indicating early development; uncertainty quantification is an evolving field with emerging best practices.

overlap_note:
  Minimal overlap with other drafts; focuses specifically on uncertainty quantification rather than safety or inference frameworks.

momentum_note:
  Moderate momentum as uncertainty quantification gains importance in AI governance, though still developing consensus on methodologies.

relevance_note:
  Highly relevant for trustworthy AI deployment; uncertainty quantification is critical for safety-critical applications and regulatory compliance.


draft_name: iso-iec-cd-ts-22440-1
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:37.268774+00:00
summary:
  Specifies requirements for integrating functional safety with AI systems as part 1 of a three-part standard. Focuses on what safety requirements AI systems must meet.

novelty_note:
  Bridges traditionally separate domains of functional safety (from IEC 61508 lineage) and AI, addressing critical need for safety-critical AI deployment.

maturity_note:
  At CD (Committee Draft) stage; functional safety principles are well-established but their application to AI systems is still being standardized.

overlap_note:
  Moderate overlap with Part 2 and 3; together they form a comprehensive safety framework but individually focused on different aspects.

momentum_note:
  Strong momentum given increasing deployment of AI in safety-critical domains (automotive, medical, industrial control).

relevance_note:
  Critically relevant for any AI deployment in regulated, safety-critical industries; foundational for responsible AI systems.


draft_name: iso-iec-cd-ts-22440-2
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:37.278333+00:00
summary:
  Provides guidance on implementing functional safety with AI systems as part 2 of three-part standard. Offers practical advice on how to meet safety requirements.

novelty_note:
  Complements Part 1 by translating safety requirements into actionable guidance; fills gap between abstract requirements and implementation.

maturity_note:
  At CD stage; guidance is developing alongside requirements; maturity dependent on industrial feedback and practical validation.

overlap_note:
  Moderate overlap with Part 1 and 3; Part 2 sits between abstract requirements and concrete examples in the standard trilogy.

momentum_note:
  Strong momentum as practitioners seek clear guidance for safety-critical AI implementation in regulated industries.

relevance_note:
  Highly relevant for practitioners implementing safety-critical AI systems; provides bridge between requirements and application.


draft_name: iso-iec-cd-ts-22440-3
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:37.287477+00:00
summary:
  Provides concrete examples and case studies for applying functional safety to AI systems as part 3 of three-part standard. Demonstrates implementation in real-world scenarios.

novelty_note:
  Examples add practical value by showing how abstract safety principles apply across different AI application domains and industries.

maturity_note:
  At CD stage; examples-focused standards have lower maturity until comprehensive real-world case studies are validated and included.

overlap_note:
  Moderate overlap with Parts 1 and 2; Part 3 illustrates concepts from earlier parts but with domain-specific variations.

momentum_note:
  Moderate momentum; value of examples grows as standard matures and organizations need guidance on implementation.

relevance_note:
  Relevant for organizations seeking concrete guidance on applying safety standards; most useful when combined with Parts 1 and 2.


draft_name: iso-iec-awi-ts-25258
categories: ["Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:17:37.296342+00:00
summary:
  Provides guidance on hybrid AI inference frameworks for multi-task AI systems in deployment. Addresses how AI systems generate outputs using multiple inference approaches.

novelty_note:
  Focuses on practical inference deployment for hybrid AI approaches; moderately novel as deployment frameworks are emerging area but build on established ML serving patterns.

maturity_note:
  At early AWI stage with minimal abstract detail; maturity will depend on how well it addresses emerging hybrid AI system complexities.

overlap_note:
  Minimal overlap with other drafts; unique focus on hybrid inference frameworks rather than safety, uncertainty, or requirements.

momentum_note:
  Limited momentum shown; hybrid AI frameworks are niche area; broader adoption depends on validation of approach effectiveness.

relevance_note:
  Moderately relevant for organizations deploying multi-task or ensemble AI systems; less critical than safety or governance standards.


draft_name: iso-cd-25268
categories: ["Autonomous netops", "Other AI/agent"]
rated_at: 2026-03-08T17:17:49.158875+00:00
summary:
  Guidelines for implementing autonomous mobile robots in hospital internal logistics for pharmaceutical delivery. Covers physical AMR design, medication packaging, delivery chambers, emergency procedures, and hospital logistics environments including elevator sequences and delivery locations.

novelty_note:
  Niche application domain (hospital pharma logistics) with moderate novelty; combines existing AMR concepts with healthcare-specific requirements

maturity_note:
  Committee draft stage suggests early development; healthcare logistics is specialized but AMR technology is mature

overlap_note:
  Minimal overlap with other drafts; highly domain-specific to hospital logistics rather than general AI/agent standards

momentum_note:
  Limited momentum indicators; niche market for hospital AMR logistics may restrict broader adoption and standardization pressure

relevance_note:
  Relevant to healthcare organizations and AMR manufacturers but limited to specific vertical; medium relevance for broader AI standardization ecosystem


draft_name: iso-iec-cd-42007
categories: ["AI safety/alignment", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:17:49.169732+00:00
summary:
  High-level framework and guidance for developing conformity assessment and certification schemes for AI systems. Addresses how to establish certification processes and schemes for AI system evaluation.

novelty_note:
  Novel governance framework for AI system certification; addresses critical standardization gap in how AI systems are assessed and certified

maturity_note:
  Committee draft indicates active development with stakeholder engagement; foundational nature suggests need for broader consensus

overlap_note:
  Some overlap with AI safety/alignment concerns but primarily focused on assessment methodology rather than specific safety properties

momentum_note:
  High momentum as AI regulation and certification requirements drive standardization needs across industries and jurisdictions

relevance_note:
  Highly relevant; foundational standard for AI system assessment applicable across multiple sectors and regulatory contexts


draft_name: iso-awi-tr-24492
categories: ["Policy/governance", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:17:49.177745+00:00
summary:
  Technical report identifying standardization needs for applying artificial intelligence in the financial services industry. Focuses on gaps and requirements specific to AI adoption in financial services.

novelty_note:
  Domain-specific needs assessment for financial AI; identifies sector-specific standardization gaps but limited core technical novelty

maturity_note:
  Early stage (AWI/TR) indicates preliminary investigation; financial AI regulation is rapidly evolving affecting standard maturity

overlap_note:
  Moderate overlap with broader AI governance standards but focused on financial sector specifics; complements rather than duplicates

momentum_note:
  Strong momentum driven by regulatory pressure on financial institutions to adopt and govern AI responsibly

relevance_note:
  Highly relevant to financial sector but narrower applicability than horizontal AI standards; important for compliance-driven industries


draft_name: iso-iec-awi-25505
categories: ["A2A protocols", "Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:17:49.186341+00:00
summary:
  International standard for wireless charging communication protocols for autonomous moving machines. Defines architecture, message frameworks, and logical communication structures above MAC layer for energy transfer coordination across heterogeneous networks.

novelty_note:
  Novel focus on wireless energy transfer as critical infrastructure for autonomous systems; addresses emerging operational dependency not previously standardized

maturity_note:
  AWI stage with multi-part planned development suggests complex standardization; wireless charging technology still maturing for autonomous systems

overlap_note:
  Highly unique; addresses specific technical infrastructure need with minimal overlap to other standards listed

momentum_note:
  Moderate momentum from growing AMM/autonomous vehicle market requiring charging infrastructure; not yet mainstream priority

relevance_note:
  Relevant to autonomous system viability but operationally focused; essential for autonomous logistics but indirect relationship to broader AI standards


draft_name: iso-iec-awi-tr-25523
categories: ["Data formats/interop", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:17:49.195352+00:00
summary:
  Technical report providing overview of data profiles for analytics and machine learning applications. Examines data format and profile standards relevant to ML and analytics in information technology systems.

novelty_note:
  Low novelty; data formats and profiles for ML are well-explored; primarily synthesis and overview of existing practices

maturity_note:
  Early stage TR; data format standardization is mature concept but ML-specific profiles may lack consensus

overlap_note:
  Substantial overlap with general data interoperability and ML infrastructure standards; covers ground well-trodden in data standardization

momentum_note:
  Low momentum; horizontal data standards face competing de-facto standards (JSON, Parquet, etc.) reducing standardization urgency

relevance_note:
  Moderately relevant as foundational infrastructure for ML systems but limited differentiation; general-purpose rather than addressing specific gaps


draft_name: iso-iec-awi-ts-25566
overlap_note: Terminology work is somewhat unique; minor overlap with general AI governance frameworks
momentum_note: Part of larger ISO/IEC AI standards initiative; moderate momentum as foundational standard
relevance_note: High relevance for standardizing AI engineering practices globally; critical for interoperability
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:17:59.604214+00:00
summary:
  Establishes standard terminology and conceptual frameworks for domain engineering in AI systems. Targets organizations across sectors developing, providing, or using AI systems. Foundational reference work for consistent AI engineering vocabulary.

novelty_note:
  Domain engineering terminology in AI is emerging; moderate novelty in systematizing existing practices into ISO standard form

maturity_note:
  Early-stage technical specification (AWI status); needs broader stakeholder input and testing before maturity


draft_name: iso-iec-awi-ts-25568
maturity_note: Early AWI stage; generative AI landscape evolving faster than standards maturation
overlap_note: Generative AI risk guidance is relatively unique; some overlap with general AI safety principles
momentum_note: High momentum given urgent industry need for generative AI risk frameworks
relevance_note: Critical relevance as generative AI adoption accelerates; addresses immediate safety concerns
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:59.616370+00:00
summary:
  Provides systematic guidance on identifying, analyzing, and treating risks specific to generative AI systems. Covers risk sources, stakeholders, and lifecycle-based control mechanisms. Addresses emerging risks from generative capabilities.

novelty_note:
  Generative AI risk frameworks are novel; this document fills timely gap in systematic risk guidance for rapidly evolving technology


draft_name: iso-iec-awi-ts-25569
overlap_note: Moderate overlap with data privacy standards (GDPR, etc.); adds ML-specific perspective
momentum_note: Steady momentum driven by privacy regulation compliance needs
relevance_note: High relevance for organizations managing sensitive data in ML; addresses regulatory requirements
categories: ["Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:17:59.627405+00:00
summary:
  Offers practical implementation guidance on de-identifying data for machine learning model development. Covers methods applicable throughout ML pipeline. Bridges privacy requirements with ML engineering practices.

novelty_note:
  De-identification in ML context is moderately novel; combines established privacy techniques with ML-specific considerations

maturity_note:
  Mid-stage development; practical methods exist but standardized implementation guidance is still emerging


draft_name: iso-iec-awi-ts-25570
momentum_note: Moderate momentum as reliability becomes critical concern for AI deployment
relevance_note: High relevance for mission-critical AI deployments; essential for assurance and compliance
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:17:59.637694+00:00
summary:
  Provides statistical methods and metrics for assessing AI system reliability. Includes procedures for reliability evaluation from quantitative perspective. Enables systematic reliability measurement.

novelty_note:
  AI reliability metrics are moderately novel; applies classical reliability engineering to AI domain with new considerations

maturity_note:
  Early AWI stage; statistical approaches exist but AI-specific reliability frameworks still developing

overlap_note:
  Relatively unique in AI context; builds on classical reliability engineering with limited direct overlap


draft_name: iso-iec-awi-ts-25571
overlap_note: Moderate overlap with broader AI ethics frameworks and governance documentation practices
momentum_note: Lower momentum; ethical documentation valuable but less urgent than safety/risk guidance
relevance_note: Relevant for organizations formalizing ethics processes; moderately important for governance
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:17:59.647339+00:00
summary:
  Provides template and instructions for documenting ethical issues across AI system lifecycle stages. Practical tool for stakeholders to identify and record ethical considerations. Facilitates systematic ethical governance.

novelty_note:
  Ethical documentation templates are incremental; applies existing ethics frameworks to structured documentation format

maturity_note:
  Early AWI stage; template-based approach is practical but lacks empirical validation across diverse contexts


draft_name: iso-iec-cd-tr-18988
overlap_note: Limited overlap with other drafts; domain-specific rather than foundational infrastructure focus
momentum_note: Early stage (CD) with healthcare focus may limit broader adoption momentum outside medical sector
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:20:47.352977+00:00
summary:
  Technical report on applying AI technologies within health informatics systems. Covers standards for AI deployment in healthcare contexts.

novelty_note:
  Health-specific AI application guidance; moderate novelty as domain-focused variant of broader AI standards

maturity_note:
  Committee draft stage indicates moderate maturity; health informatics adds specificity but builds on established AI frameworks

relevance_note:
  Relevant for healthcare AI deployment but niche applicability compared to general AI infrastructure standards


draft_name: iso-awi-tr-3510
overlap_note: Highly unique to mining sector; minimal overlap with other AI/agent infrastructure standards
momentum_note: Niche industrial application may limit cross-sector momentum and adoption velocity
relevance_note: Relevant for autonomous mining but limited applicability to broader AI agent ecosystems
categories: ["A2A protocols", "Autonomous netops", "Data formats/interop"]
rated_at: 2026-03-08T17:20:47.362563+00:00
summary:
  Standard for communication interfaces enabling interoperability between supervisor systems and heterogeneous autonomous controllers in mining. Addresses A2A protocol requirements.

novelty_note:
  Mining-specific autonomous coordination; novel application domain but follows established interoperability patterns

maturity_note:
  Early stage (AWI) with domain-specific focus; technical maturity depends on mining automation precedents


draft_name: iso-iec-awi-25589
relevance_note: Highly relevant; human-machine teaming is critical for responsible AI deployment across industries
categories: ["Human-agent interaction", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:20:47.372585+00:00
summary:
  Framework defining concepts, design principles, and technical characteristics for human-machine teaming. Provides guidance for integrating human interaction with machine intelligence.

novelty_note:
  Strong novelty in systematizing human-machine collaboration; advances beyond traditional human-in-loop patterns with formal framework

maturity_note:
  AWI stage with comprehensive scope; framework provides conceptual maturity though implementation guidance may vary

overlap_note:
  Moderate overlap with 25590 on AI output quality; complements but distinct from model-focused standards

momentum_note:
  High momentum as human-AI teaming is active research area; broad applicability across sectors increases adoption potential


draft_name: iso-iec-awi-25590
categories: ["AI safety/alignment", "Model serving/inference", "Policy/governance"]
rated_at: 2026-03-08T17:20:47.383126+00:00
summary:
  Provides guidance for measuring and assessing output data quality from generative AI applications. Addresses quality considerations from creation, use, and impact perspectives.

novelty_note:
  Novel focus on generative AI output quality assessment; timely response to emerging generative AI deployment challenges

maturity_note:
  AWI stage indicates framework development underway; quality metrics for generative systems still maturing industry-wide

overlap_note:
  Complements 25589 on human-machine interaction; overlaps with model description (25623) but distinct quality focus

momentum_note:
  Highest momentum; generative AI output quality is urgent concern; strong stakeholder interest across sectors

relevance_note:
  Extremely relevant; output quality directly impacts safety, trustworthiness, and responsible AI deployment


draft_name: iso-iec-awi-25623
relevance_note: Relevant for organizations managing ML lifecycle; foundational for interoperability and governance
categories: ["Data formats/interop", "Model serving/inference", "Policy/governance"]
rated_at: 2026-03-08T17:20:47.391937+00:00
summary:
  Establishes a description framework and documentation elements for ML models across their lifecycle. Supports model management and usage across organizations.

novelty_note:
  Moderate novelty; ML model documentation frameworks exist but standardization adds value for lifecycle management

maturity_note:
  AWI stage; framework concept mature but comprehensive adoption and standardized implementation still developing

overlap_note:
  Minimal overlap; model description complements but distinct from quality guidance (25590) and human-machine teaming (25589)

momentum_note:
  Steady momentum; model documentation is recognized need but lacks urgency of generative AI quality concerns


draft_name: iso-iec-awi-42003
novelty_note: Implementation guidance is derivative of existing 42001 standard; limited novel technical content
maturity_note: Well-established foundational work building on mature 42001 framework
overlap_note: Moderate overlap with other governance and management system standards in ISO/IEC AI portfolio
momentum_note: Active development with clear practical applications for organizations adopting AI systems
relevance_note: High relevance for organizations implementing formal AI governance and management practices
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:20:57.098520+00:00
summary:
  Provides implementation guidance for ISO/IEC 42001 AI management systems standard. Addresses competencies needed for AIMS professionals across organizations of all types and sizes.


draft_name: iso-dis-42501
novelty_note: Applies established safety/trustworthiness concepts to sharing economy context; moderate novelty
maturity_note: Fairly mature domain-specific application though sharing economy platforms continue evolving
momentum_note: Steady progress but narrower scope than broader AI safety initiatives
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:20:57.109513+00:00
summary:
  Establishes trustworthiness and safety requirements for digital platform operators in the sharing economy. Applies to platform governance rather than underlying system architecture.

overlap_note:
  Limited overlap; specialized focus on sharing economy platforms distinguishes from broader AI safety standards

relevance_note:
  Relevant for sharing economy operators and platform governance but narrower audience than general AI standards


draft_name: iso-iec-awi-ts-42119-7
maturity_note: Early-stage technical guidance; red teaming practices for AI still evolving and maturing
overlap_note: Minimal overlap; red teaming guidance is distinct from other AI testing and safety standards
categories: ["AI safety/alignment"]
rated_at: 2026-03-08T17:20:57.118484+00:00
summary:
  Provides technology-agnostic guidance for conducting red teaming assessments on AI systems. Covers risk identification, methodologies, documentation, and lifecycle integration aligned with ISO/IEC 29119.

novelty_note:
  Red teaming for AI is emerging area with novel assessment methodologies not fully standardized elsewhere

momentum_note:
  Strong momentum driven by heightened focus on AI robustness, adversarial testing, and safety validation

relevance_note:
  Highly relevant as organizations increasingly prioritize adversarial testing and AI system robustness


draft_name: iso-iec-awi-25704
maturity_note: Builds on mature process assessment frameworks but AI lifecycle application still developing
overlap_note: Significant overlap with ISO/IEC 42001 governance frameworks and other AI lifecycle standards
momentum_note: Moderate progress; process assessment maturity models gaining traction in AI governance
relevance_note: Relevant for organizations seeking to measure and improve AI development and deployment processes
categories: ["Policy/governance"]
rated_at: 2026-03-08T17:20:57.126622+00:00
summary:
  Defines process assessment model for evaluating AI system lifecycle process capability. Provides measurement framework and indicators for determining organizational AI process maturity levels.

novelty_note:
  Applies established process assessment methodology (ISO/IEC 33020) to AI domain; incremental rather than novel


draft_name: iso-cd-21520
maturity_note: Mature P3M practices with emerging AI integration; foundational content still being standardized
overlap_note: Moderate-high overlap with governance, policy, and organizational AI management standards
momentum_note: Steady adoption of AI in P3M contexts but narrower focus than broader AI standards
relevance_note: Relevant for P3M practitioners and organizations managing projects with AI components
categories: ["Policy/governance", "Human-agent interaction"]
rated_at: 2026-03-08T17:20:57.134840+00:00
summary:
  Outlines AI concepts, applications, and implications for project, programme, and portfolio management. Provides governance framework and guidance on security, privacy, bias, and ethics for P3M organizations.

novelty_note:
  Applies AI to established P3M discipline; limited novel AI technical content, mostly domain adaptation


draft_name: iec-np-ts-62366-3
categories: ["Policy/governance", "Human-agent interaction", "AI safety/alignment"]
rated_at: 2026-03-08T17:21:09.147091+00:00
summary:
  Guidance document for applying usability engineering processes to medical devices using AI/ML technology. Builds on IEC 62366-1 standards with specific considerations for AI-based medical device development.

novelty_note:
  Applies existing usability framework to emerging AI/ML medical device domain; moderate novelty in specialization rather than new concepts

maturity_note:
  Technical specification stage with established parent standard (IEC 62366-1); guidance-focused approach indicates mature thinking

overlap_note:
  Unique focus on medical device usability with AI/ML; minimal overlap with other AI governance/testing standards listed

momentum_note:
  Technical specification status suggests slower progress; niche medical device focus limits broader AI community momentum

relevance_note:
  Relevant for medical device sector specifically; human-device interaction aspects valuable but limited general AI applicability


draft_name: iso-iec-awi-ts-42119-8
categories: ["AI safety/alignment", "Model serving/inference", "Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:21:09.156581+00:00
summary:
  Quality assessment framework for generative AI text-to-text systems using prompt-based approaches. Covers testing methodologies including red teaming, safety considerations, and results interpretation.

novelty_note:
  Addresses emerging generative AI testing gap; red teaming methodology and prompt-based assessment represent novel standardization areas

maturity_note:
  AWI (Advanced Work Item) stage indicates early development; builds on existing standards (23282, 42119-7) suggesting incremental maturity

overlap_note:
  Moderate overlap with AI safety/alignment and testing approaches; complements resilience assessment drafts

momentum_note:
  Generative AI focus aligns with current technology momentum; prompt engineering and LLM testing are high-priority areas

relevance_note:
  Highly relevant to current AI deployment challenges; directly addresses practical quality assessment for widely-deployed generative systems


draft_name: iso-iec-awi-25870
categories: ["Policy/governance", "AI safety/alignment", "Data formats/interop"]
rated_at: 2026-03-08T17:21:09.165847+00:00
summary:
  Framework specifying data elements for reporting AI incidents across all organization types. Establishes standardized incident documentation structure.

novelty_note:
  Incident reporting structure is relatively straightforward; value lies in cross-organizational standardization rather than conceptual novelty

maturity_note:
  AWI status; incident reporting frameworks are established in other domains but AI-specific application is nascent

overlap_note:
  Unique incident reporting focus; complements but distinct from safety/resilience assessment standards

momentum_note:
  Growing awareness of AI incident tracking needs; momentum moderate as field still establishing incident reporting culture

relevance_note:
  Increasingly relevant as AI systems proliferate; incident data collection critical for safety and governance across sectors


draft_name: iso-iec-awi-25872-1
categories: ["Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:21:09.177428+00:00
summary:
  Framework and guidance for knowledge enhancement methods applied to pretrained machine learning models. Part 1 establishes conceptual foundations and enhancement methodologies.

novelty_note:
  Knowledge enhancement is emerging field; framework development moderate novelty as techniques exist but standardization is new

maturity_note:
  Early AWI stage with multi-part structure; foundational framework indicates work still in formulation phase

overlap_note:
  Unique focus on knowledge enhancement for pretrained models; minimal overlap with other listed standards

momentum_note:
  Specialized technical area with limited mainstream momentum; applicable primarily to ML practitioners seeking model improvement

relevance_note:
  Moderately relevant for ML development lifecycle; practical applicability concentrated in model optimization domain


draft_name: iso-iec-awi-ts-25864
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:21:09.188459+00:00
summary:
  Comprehensive framework providing methods, mechanisms, guidelines, and quantifiable metrics for assessing AI system resilience. Addresses robustness and failure modes.

novelty_note:
  Resilience assessment for AI systems represents emerging standardization need; quantifiable metrics approach is novel contribution

maturity_note:
  AWI TS (Technical Specification) stage indicates developed thinking; resilience frameworks exist in traditional systems but AI-specific adaptation is intermediate

overlap_note:
  Moderate overlap with AI safety/alignment and testing standards; complementary to incident reporting and quality assessment drafts

momentum_note:
  AI resilience and robustness are high-priority current topics; momentum strong as deployments increase demand for reliability guarantees

relevance_note:
  Highly relevant across sectors; resilience metrics essential for critical infrastructure and safety-sensitive AI applications


draft_name: iso-iec-awi-tr-24030
categories: ["Other AI/agent", "Policy/governance"]
rated_at: 2026-03-08T17:21:20.605567+00:00
summary:
  Compiles representative use cases of AI applications across various domains to inform standardization efforts. Provides practical examples of AI deployment scenarios without prescriptive requirements.

novelty_note:
  Use case collection is foundational but not technically novel; primarily serves as reference material for standards development

maturity_note:
  Early stage technical report (TR) with abstract content; lacks detailed implementation guidance or maturity examples

overlap_note:
  Minimal overlap with other drafts; serves as complementary reference material rather than addressing specific technical standards

momentum_note:
  Moderate momentum as foundational input to AI standardization; useful for scoping but not directly advancing technical specifications

relevance_note:
  Highly relevant for understanding AI application landscape and identifying standardization needs across domains


draft_name: iso-iec-np-25880
relevance_note: Critical relevance for safe and effective AI deployment where human judgment remains essential
categories: ["Human-agent interaction", "Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:21:20.617021+00:00
summary:
  Specifies organizational requirements and guidance for implementing human-machine teaming in AI systems during practical operation. Addresses how human operators and AI systems collaborate within organizations.

novelty_note:
  Focuses on organizational and procedural aspects of HMT; novel in formalizing team dynamics but builds on established human-factors principles

maturity_note:
  New proposal stage (NP) with clear scope but limited detail; requires substantive development before full standardization

overlap_note:
  Moderate overlap with human-agent interaction concerns; some alignment with ISO/AWI 25922 on human-machine allocation

momentum_note:
  Growing momentum as AI systems increasingly require human oversight; directly addresses practical implementation gaps


draft_name: iso-awi-tr-25896
relevance_note: Low-to-moderate relevance outside terminology standardization community; niche application area
categories: ["Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:21:20.627066+00:00
summary:
  Addresses application of AI techniques to terminology resource management and standardization. Combines terminology management standards with AI-enabled tools for language and concept handling.

novelty_note:
  Applies existing AI concepts to specialized domain (terminology); incremental rather than fundamentally novel

maturity_note:
  Early working draft stage; narrow applicability to specialized ISO/TC 37 community limits mainstream relevance

overlap_note:
  Highly unique focus on terminology management; minimal overlap with other AI standardization efforts

momentum_note:
  Limited momentum; narrow domain relevance and specialized audience reduces driving force for progression


draft_name: iso-iec-awi-25058
categories: ["Policy/governance", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:21:20.636777+00:00
summary:
  Provides measurement methods and quality evaluation guidance for AI systems using quality models defined in ISO/IEC 25059. Establishes metrics and processes for assessing AI system quality across organizations.

novelty_note:
  Novel in formalizing quality measurement for AI systems; extends traditional SQuaRE framework to AI-specific concerns

maturity_note:
  Working draft stage with reference to companion standard (25059); substantive but requires refinement of measurement approaches

overlap_note:
  Low overlap; specialized quality measurement focus distinct from other standards, though somewhat related to safety/alignment frameworks

momentum_note:
  Strong momentum as organizations need standardized AI quality assessment; addresses critical gap in evaluation practices

relevance_note:
  Highly relevant for organizations developing and deploying AI systems; essential for quality assurance and governance


draft_name: iso-awi-25922
categories: ["Human-agent interaction", "Autonomous netops", "Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:21:20.687216+00:00
summary:
  Specifies methods for defining and allocating capabilities and responsibilities between maritime autonomous surface ships (MASS) and remote human operators. Establishes standardized approaches for human-machine task allocation in maritime automation.

novelty_note:
  Novel in formalizing MASS operator interaction; applies human-machine teaming principles to critical maritime domain with safety implications

maturity_note:
  Working draft with clear scope and practical maritime context; moderately mature but requires validation through maritime industry input

overlap_note:
  Significant overlap with ISO/IEC NP 25880 on human-machine teaming principles; both address capability/responsibility allocation

momentum_note:
  Moderate momentum driven by maritime industry autonomous systems development; domain-specific rather than broadly transformative

relevance_note:
  Highly relevant for maritime industry and autonomous systems safety; moderate broader relevance for human-agent interaction principles


draft_name: iso-awi-25934
momentum_note: Niche maritime focus limits broad momentum; relevance primarily to shipping industry stakeholders
categories: ["Autonomous netops", "Policy/governance", "Data formats/interop"]
rated_at: 2026-03-08T17:21:31.441938+00:00
summary:
  Establishes structured verification procedures for autonomous navigation systems in Maritime Autonomous Surface Ships (MASS). Addresses safety and reliability assessment across different operational modes, supporting manufacturers, operators, and regulators in developing MASS-specific verification frameworks.

novelty_note:
  Verification procedures for maritime autonomous systems are specialized; moderate novelty in applying ISO safety standards to MASS domain

maturity_note:
  Early stage (AWI=Active Work Item); framework still under development with limited implementation guidance

overlap_note:
  Overlaps with general autonomous system verification standards but maritime-specific niche reduces overlap

relevance_note:
  Relevant to autonomous maritime operations but limited to specific vertical; emerging regulatory importance


draft_name: iso-iec-cd-30147
momentum_note: IoT trustworthiness is active area; moderate momentum but integration with 15288 is specialized
relevance_note: High relevance to IoT system engineering; applicable across IoT verticals
categories: ["Data formats/interop", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:21:31.450931+00:00
summary:
  Integrates IoT trustworthiness verification activities into ISO/IEC/IEEE 15288 system engineering processes. Bridges IoT-specific security and reliability concerns with established systems engineering methodologies.

novelty_note:
  Integration of trustworthiness into established SE processes shows moderate novelty; trustworthiness frameworks exist but process integration is somewhat novel

maturity_note:
  Committee Draft stage indicates substantive development; closer to standardization than early-stage work

overlap_note:
  Significant overlap with existing ISO/IEC/IEEE 15288 and other IoT security standards; incremental refinement


draft_name: iso-awi-tr-19182
maturity_note: Technical Report (TR) in AWI stage; exploratory guidance rather than normative standard
overlap_note: Bridges GIS and AI domains with some overlap to broader AI standards and geospatial data standards
momentum_note: GeoAI gaining attention but geographic information standards community is relatively specialized
relevance_note: Relevant to GIS practitioners and location-based AI applications; moderate general relevance
categories: ["Data formats/interop", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:21:31.459036+00:00
summary:
  Provides guidance on incorporating Geospatial Artificial Intelligence (GeoAI) into geographic information standards. Addresses integration of AI techniques within GIS and geospatial data frameworks.

novelty_note:
  GeoAI is emerging field; guidance on standards integration is moderately novel but builds on existing AI and GIS standards


draft_name: iso-iec-awi-23888-5
maturity_note: Early AWI stage with minimal abstract detail; technical specifications still under development
overlap_note: Relatively unique focus on AI-based dynamic compression; limited overlap with existing standards
relevance_note: Relevant to 3D imaging, robotics, autonomous systems; emerging application domains
categories: ["Data formats/interop", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:21:31.468003+00:00
summary:
  Defines bitstream syntax, semantics, and decoding procedures for AI-based dynamic point cloud compression. Specifies encoding format and reconstruction methods for efficient point cloud representation.

novelty_note:
  Dynamic point cloud compression with AI is novel; combines emerging compression techniques with point cloud standards

momentum_note:
  3D/point cloud processing gaining momentum; AI-based compression increasingly important for multimedia


draft_name: iso-iec-awi-23888-4
relevance_note: Highly relevant to video analytics, edge ML, autonomous systems requiring video understanding
categories: ["Data formats/interop", "Model serving/inference", "ML traffic mgmt"]
rated_at: 2026-03-08T17:21:31.476862+00:00
summary:
  Defines bitstream format and decoding process for compression of machine-extracted video features. Optimizes feature coding for efficiency in bitrate, machine task performance, and computational complexity.

novelty_note:
  Feature coding for machines (vs. humans) is relatively novel; focuses on ML-optimized compression rather than human perception

maturity_note:
  Early AWI stage with limited specification detail; framework and requirements still being formulated

overlap_note:
  Unique focus on machine-centric feature compression; minimal overlap with human-centric video standards

momentum_note:
  ML inference efficiency and edge computing drive momentum; feature compression increasingly relevant


draft_name: iso-iec-awi-26090-1
momentum_note: Early development stage limits momentum indicators; city knowledge domain is emerging area
categories: ["Policy/governance", "AI safety/alignment", "Data formats/interop"]
rated_at: 2026-03-08T17:21:42.592591+00:00
summary:
  Establishes framework for evaluating trustworthiness of city knowledge systems in smart city contexts. Covers concepts, characteristics, methodology, and use cases for knowledge trustworthiness assessment.

novelty_note:
  Applies trustworthiness evaluation specifically to city/urban knowledge domains; moderately novel framing for smart cities context

maturity_note:
  Early stage AWI (Advanced Work Item) with foundational overview content; lacks detailed technical specifications

overlap_note:
  Moderate overlap with general AI evaluation frameworks; distinct urban/city knowledge focus reduces overlap

relevance_note:
  Relevant for smart city deployments and urban data governance; limited relevance to broader AI systems


draft_name: iso-iec-awi-26160
maturity_note: Builds on established CC/CEM frameworks; AIspecific extensions are in development stage
overlap_note: Low overlap; uniquely bridges security evaluation standards with AI functionality assessment
momentum_note: Addresses critical security evaluation gap; strong momentum from established CC ecosystem
relevance_note: Highly relevant for regulated AI deployments; essential for security-critical AI systems evaluation
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:21:42.602824+00:00
summary:
  Extends ISO/IEC 15408 (Common Criteria) and ISO/IEC 18045 evaluation methodologies with AI-specific security assurance and functional requirements. Focuses on security evaluation of AI systems.

novelty_note:
  Novel adaptation of mature security evaluation standards to AI context; addresses significant gap in AI security assurance


draft_name: iso-iec-pwi-26200
maturity_note: Early PWI (Proposal Work Item) stage; LLM field evolving rapidly, standard maturity uncertain
rated_at: 2026-03-08T17:21:42.611276+00:00
summary:
  Proposes comprehensive standard for LLM evaluation, ethical governance, interoperability, testing methodologies, bias mitigation, and secure deployment across domains. Scope limited to open, general-purpose LLMs.

novelty_note:
  Moderately novel; consolidates existing LLM evaluation practices into single standard; interoperability focus adds value

overlap_note:
  Significant overlap with emerging LLM evaluation frameworks and guidelines; covers well-trodden ground

momentum_note:
  LLM standardization is active area; proposal timing good but faces competition from de facto standards

relevance_note:
  Extremely relevant; LLMs are dominant AI deployment model; covers healthcare, finance, education sectors

categories:
  ["AI safety/alignment", "Policy/governance", "Model serving/inference", "Data formats/interop", "Human-agent interaction"]


draft_name: iso-np-ts-25280-1
overlap_note: Low overlap; unique focus on records management dimension of AI rather than AI evaluation itself
momentum_note: Records management + AI is emerging concern; early development stage limits momentum visibility
categories: ["Policy/governance", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:21:42.619309+00:00
summary:
  Establishes principles and considerations for records management in AI-enabled environments, covering both AI-generated and AI-associated records across all organization types.

novelty_note:
  Moderately novel application of records management to AI context; fills gap in documentation standards for AI systems

maturity_note:
  Early NP (New Proposal) stage with principles-level guidance; lacks detailed implementation specifications

relevance_note:
  Moderately relevant for compliance and governance; critical for regulated sectors; less relevant for AI capabilities


draft_name: iso-np-ts-25280-2
novelty_note: Moderately novel; focuses on AI-as-tool for records rather than records-of-AI; complements Part 1
maturity_note: Early NP stage with principles-level content; application-specific but not detailed implementation
momentum_note: Early stage; records automation is mature domain, AI application is incremental advancement
relevance_note: Limited relevance outside records/information management domain; niche application focus
categories: ["Policy/governance", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:21:42.627261+00:00
summary:
  Outlines principles and considerations for applying AI capabilities to records management functions, controls, processes, and systems across all organization types.

overlap_note:
  Low overlap; distinct from Part 1; narrow focus on records automation reduces overlap with broader AI standards


draft_name: iso-awi-26253
rated_at: 2026-03-08T17:22:01.791032+00:00
summary:
  Guidelines for implementing centralized control systems for autonomous mobile robots managing pharmaceutical logistics in hospitals. Covers safe operation, real-time monitoring, communication, scheduling, and record-keeping for AMR-based internal hospital logistics.

novelty_note:
  Specialized application domain (hospital pharma logistics) with established AMR technology; moderate novelty in standardizing hospital-specific CCS requirements

maturity_note:
  Well-defined problem space with mature robotics foundations; practical operational focus suggests implementation-ready guidance

overlap_note:
  Minimal overlap with other AI/agent standards; niche healthcare robotics focus distinct from broader AI governance and NLP work

momentum_note:
  Healthcare automation is active area; pharmaceutical supply chain efficiency has ongoing industry momentum

relevance_note:
  High relevance for healthcare organizations and medical device manufacturers; addresses critical operational safety and logistics coordination

categories:
  ["Autonomous netops", "ML traffic mgmt", "Agent identity/auth", "Policy/governance", "Human-agent interaction"]


draft_name: iso-iec-22989-2022-awi-amd-2
categories: ["Data formats/interop", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:22:01.801620+00:00
summary:
  Amendment 2 to ISO/IEC 22989:2022 updating AI concepts and terminology standards. Incremental refinement of existing AI vocabulary and definitions framework.

novelty_note:
  Maintenance amendment to established standard; minimal substantive novelty expected in terminology updates

maturity_note:
  Mature foundational standard with established terminology; amendment represents evolution of stable reference material

overlap_note:
  Heavy conceptual overlap with companion ISO/IEC 23053 amendment and other AI/ML standards relying on shared terminology

momentum_note:
  Routine standards maintenance; incremental updates typically lower industry momentum than new frameworks

relevance_note:
  High relevance as foundational reference for AI terminology across all sectors and standards development


draft_name: iso-iec-23053-2022-awi-amd-2
novelty_note: Maintenance amendment to established ML systems framework; limited novelty in framework evolution
maturity_note: Mature framework standard with established guidance; amendment represents incremental maturation
momentum_note: Standards maintenance activity; routine updates show stable but not accelerating momentum
categories: ["Model serving/inference", "Policy/governance", "Data formats/interop", "Other AI/agent"]
rated_at: 2026-03-08T17:22:01.810545+00:00
summary:
  Amendment 2 to ISO/IEC 23053:2022 updating the AI/ML systems framework. Incremental refinement to existing framework for AI systems using machine learning approaches.

overlap_note:
  Significant overlap with companion ISO/IEC 22989 amendment and broad alignment with other ISO/IEC AI standards

relevance_note:
  High relevance as core reference framework for ML systems implementation across organizations and sectors


draft_name: iso-iec-np-ts-26312
categories: ["AI safety/alignment", "Policy/governance", "Human-agent interaction", "Other AI/agent"]
rated_at: 2026-03-08T17:22:01.819336+00:00
summary:
  Technical specification for healthcare organizations to identify and mitigate bias in AI systems across procurement, implementation, and monitoring phases. Addresses algorithmic, data, labeling, and deployment-related bias affecting patient and clinician-facing applications.

novelty_note:
  Novel focus on healthcare-specific bias detection and mitigation; comprehensive lifecycle perspective on bias sources is relatively fresh for domain standards

maturity_note:
  Emerging practice area with developing methodologies; practical guidance framework is maturing but implementation approaches still evolving

overlap_note:
  Unique intersection of AI bias, healthcare governance, and fairness; limited direct overlap with other standards except general AI safety principles

momentum_note:
  Bias in healthcare AI is high-momentum topic; regulatory pressure and equity concerns driving strong standards development interest

relevance_note:
  Critical relevance for healthcare organizations deploying AI; addresses ethical, legal, and patient safety imperatives


draft_name: iso-iec-np-ts-26320.2
categories: ["Data formats/interop", "Model serving/inference", "Policy/governance", "Other AI/agent"]
rated_at: 2026-03-08T17:22:01.828616+00:00
summary:
  Establishes principles, frameworks, and methods for developing and maintaining corpora for natural language processing systems. Includes corpus construction requirements, application guidance, and quality evaluation measures applicable across AI system lifecycles.

novelty_note:
  Systematic approach to corpus development governance; standards for NLP data quality are valuable but building on established ML data practices

maturity_note:
  Corpus linguistics and ML data engineering are mature; standardizing corpus practices is advancing implementation maturity

overlap_note:
  Focused on NLP-specific data requirements; some overlap with general data governance but distinct from broader AI/ML standards

momentum_note:
  NLP and large language models drive sustained momentum; data quality for LLMs is active standardization priority

relevance_note:
  High relevance for organizations developing or deploying NLP systems; foundational for reproducible and fair language AI


draft_name: iso-cd-19178-2
momentum_note: Part of established ISO/TC 211 standards program; committee draft status suggests steady progress
categories: ["Data formats/interop"]
rated_at: 2026-03-08T17:22:12.636390+00:00
summary:
  Specifies JSON encoding for training data markup language in AI systems. Part of a multi-part ISO standard defining standardized formats for AI training data representation.

novelty_note:
  Incremental standardization work; JSON encoding is a common approach but application to AI training data markup is moderately novel

maturity_note:
  Committee draft stage indicates mature development; JSON is well-established technology applied to defined domain

overlap_note:
  Minimal overlap with other drafts; Part 3 covers XML variant but both are encoding-specific rather than functional

relevance_note:
  Relevant for data interoperability in AI systems; practical value depends on adoption of parent standard


draft_name: iso-cd-19178-3
momentum_note: Part of coordinated multi-part standard series; steady committee-level progress
categories: ["Data formats/interop"]
rated_at: 2026-03-08T17:22:12.647553+00:00
summary:
  Specifies XML encoding for training data markup language in AI systems. Part 3 of ISO/IEC 19178 standard for AI training data representation.

novelty_note:
  Parallel to Part 2; XML encoding is traditional approach with moderate novelty in AI training data context

maturity_note:
  Committee draft stage; XML is mature technology; development appears orderly within standards process

overlap_note:
  Functionally identical to Part 2 except for encoding format; minimal unique overlap with other drafts

relevance_note:
  Relevant for standardized AI training data interchange; XML variant provides alternative to JSON encoding


draft_name: iso-iec-np-26582
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:22:12.658577+00:00
summary:
  Defines conformity assessment requirements for functional correctness of AI systems based on ISO/IEC 25059 quality models. Applicable to all AI system types.

novelty_note:
  Novel approach to standardized AI correctness assessment; builds on quality model foundation with systematic conformity framework

maturity_note:
  New proposal stage indicates early development; references existing quality standard but conformity assessment methodology still emerging

overlap_note:
  Unique focus on functional correctness assessment; no significant overlap with other drafts in this set

momentum_note:
  New proposal indicates emerging consensus around need; but limited visibility into development momentum

relevance_note:
  Highly relevant for AI safety and governance; addresses critical need for standardized correctness evaluation across AI systems


draft_name: iso-np-26604-1
momentum_note: Emerging need driven by autonomous agricultural equipment development; early proposal stage
categories: ["Autonomous netops", "AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:22:12.668755+00:00
summary:
  Specifies safety requirements and verification methods for autonomous agricultural machinery including soil-working operations. Covers design, construction, and safe use guidance.

novelty_note:
  Applies established machinery safety standards to autonomous agriculture; domain-specific but follows conventional safety framework

maturity_note:
  New proposal stage; addresses practical safety gaps in autonomous farm equipment but methodology builds on existing machine safety standards

overlap_note:
  Highly specialized to agricultural autonomous machinery; minimal overlap with other AI/agent standards in this set

relevance_note:
  Relevant primarily for agricultural sector; limited broader applicability to general AI/agent systems


draft_name: iso-np-26609
overlap_note: Highly specialized to dental imaging; no overlap with other standards in this collection
momentum_note: Emerging need in medical AI regulation but early proposal stage indicates nascent momentum
relevance_note: Relevant for dental/medical sector; limited applicability to broader AI/agent systems and standards
categories: ["AI safety/alignment", "Policy/governance"]
rated_at: 2026-03-08T17:22:12.678744+00:00
summary:
  Sets requirements for assessing AI and Augmented Intelligence systems used with 2D dental radiographs. Domain-specific medical AI application standard.

novelty_note:
  Narrow specialization to dental radiography AI; assessment framework is incremental application of general AI principles to defined domain

maturity_note:
  New proposal; addresses specific healthcare use case but assessment methodology not substantially novel


draft_name: iso-np-pas-8800-1
maturity_note: Early-stage standard (NP/PAS status) with abstract only; foundational but incomplete specification.
relevance_note: Highly relevant for road vehicle safety governance and regulatory compliance frameworks.
categories: ["Policy/governance", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:22:23.494439+00:00
summary:
  ISO standard defining key terminology and concepts for safety and AI in road vehicles. Part 1 of a multi-part standard establishing foundational definitions for the field.

novelty_note:
  Definitions and concepts are prerequisite but not novel contributions; primarily normative clarification.

overlap_note:
  Moderate overlap with ISO 26262 and ISO 21448 safety frameworks; aligns with NIST AI RMF conceptual scope.

momentum_note:
  Emerging standard with limited adoption signals; part of active standards development but early maturity.


draft_name: iso-np-pas-8800-2
maturity_note: Incomplete abstract; still in NP/PAS development phase without finalized technical requirements.
momentum_note: Part of emerging standards initiative; unclear adoption trajectory in automotive industry.
relevance_note: Critical for automotive safety assurance and regulatory compliance in AI-enabled vehicles.
categories: ["AI safety/alignment", "Policy/governance", "Model serving/inference"]
rated_at: 2026-03-08T17:22:23.504230+00:00
summary:
  ISO standard specifying general safety requirements for AI-equipped electrical/electronic systems in production road vehicles. Addresses systematic errors, random hardware failures, and external AI element interactions.

novelty_note:
  Applies established safety methodologies to AI systems; novel integration of AI-specific failure modes with vehicle E/E safety architecture.

overlap_note:
  Significant overlap with NIST AI 100-1 risk management framework and ISO 26262 functional safety principles.


draft_name: nist-ai-100-1
categories: ["Policy/governance", "AI safety/alignment", "Human-agent interaction"]
rated_at: 2026-03-08T17:22:23.512661+00:00
summary:
  Comprehensive framework for managing AI system risks across full lifecycle, covering trustworthiness dimensions including safety, security, fairness, transparency, and accountability. Published January 2023.

novelty_note:
  Novel integrated approach combining multiple trustworthiness dimensions; establishes new governance paradigm for AI risk management.

maturity_note:
  Mature, published standard with clear structure and broad industry adoption; established reference framework.

overlap_note:
  Foundational framework with minimal overlap; complementary to domain-specific standards rather than duplicative.

momentum_note:
  Strong momentum with widespread adoption across government and private sectors; cited in policy discussions.

relevance_note:
  Essential reference framework for AI governance, risk management, and policy development across all sectors.


draft_name: nist-ai-100-2-e2025
overlap_note: Highly specialized focus with minimal overlap to other frameworks; unique in adversarial ML depth.
momentum_note: Very recent release indicates active development; strong relevance to current AI security concerns.
categories: ["AI safety/alignment", "Data formats/interop", "Model serving/inference"]
rated_at: 2026-03-08T17:22:23.522364+00:00
summary:
  Taxonomy and terminology for adversarial machine learning attacks and mitigations covering evasion, poisoning, and privacy attacks against predictive and generative AI systems. Published March 2025.

novelty_note:
  Comprehensive adversarial ML taxonomy is novel contribution; particularly detailed for LLM attack vectors.

maturity_note:
  Recent publication (2025) with mature framework; builds on established adversarial ML research with industry validation.

relevance_note:
  Highly relevant for AI safety, security, and robustness requirements; critical for LLM risk management.


draft_name: nist-ai-100-4
categories: ["Policy/governance", "Data formats/interop", "AI safety/alignment"]
rated_at: 2026-03-08T17:22:23.531109+00:00
summary:
  Guidance on managing risks from synthetic content generated by AI through authentication, provenance tracking, and content labeling mechanisms. Published July 2024.

novelty_note:
  Addresses emerging synthetic content risks; practical mitigation approaches are timely but build on existing verification techniques.

maturity_note:
  Published guidance document with practical applicability; established mitigation strategies presented in structured format.

overlap_note:
  Complementary to NIST AI 100-1; focused on specific synthetic content risks with limited overlap to other frameworks.

momentum_note:
  Recent (2024) publication addressing urgent policy concern; growing industry interest in synthetic content verification.

relevance_note:
  Increasingly relevant for content authenticity, misinformation prevention, and AI transparency requirements.


draft_name: nist-ai-600-1
maturity_note: Official NIST publication with high maturity and credibility
overlap_note: Significant overlap with NIST AI RMF base framework and general AI risk management guidance
momentum_note: Recent publication (2024) indicates active momentum in NIST's AI governance work
relevance_note: Highly relevant for AI governance, risk management, and compliance frameworks
categories: ["Policy/governance", "AI safety/alignment", "Other AI/agent"]
rated_at: 2026-03-08T17:22:33.013301+00:00
summary:
  Companion resource to NIST AI RMF that specifically addresses risks unique to or exacerbated by generative AI systems, including hallucinations, data privacy, intellectual property, and CBRN information risks. Provides practical guidance for organizations managing generative AI deployments.

novelty_note:
  Extends existing NIST AI RMF with generative AI specifics; moderate novelty as it adapts established frameworks


draft_name: nist-sp-800-218a
novelty_note: Adapts established SSDF practices to AI context; incremental novelty
maturity_note: High maturity as official NIST special publication with security focus
overlap_note: Overlaps with NIST SP 800-218 base framework and general secure development practices
momentum_note: Recent 2024 publication shows sustained focus on AI security development
relevance_note: Relevant for secure AI/ML development practices and supply chain security
categories: ["Policy/governance", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:22:33.022707+00:00
summary:
  Community profile providing secure software development practices tailored to generative AI and dual-use foundation models, addressing data management, model training, and deployment security. Builds on NIST SSDF practices for AI-specific contexts.


draft_name: nist-ir-8596
novelty_note: Applies existing CSF to AI domain; moderate novelty in mapping and adaptation
maturity_note: High maturity as NIST internal report with clear framework alignment
overlap_note: Moderate overlap with NIST CSF and other AI risk management frameworks, relatively distinct focus
momentum_note: Future-dated publication (2025) indicates planned momentum in CSF-AI integration
relevance_note: Highly relevant for cybersecurity and AI risk management integration
categories: ["Policy/governance", "AI safety/alignment"]
rated_at: 2026-03-08T17:22:33.033078+00:00
summary:
  Community profile that maps NIST Cybersecurity Framework functions to AI-specific risks and controls, enabling organizations to manage cybersecurity risks in AI systems. Bridges existing CSF with AI risk landscape.


draft_name: nist-cswp-31
novelty_note: Addresses specific technical challenge of AI V&V with proxy-based approach; relatively novel
maturity_note: Moderate maturity; technical guidance on emerging challenge with evolving best practices
overlap_note: Relatively unique focus on proxy validation/verification for AI systems
momentum_note: September 2024 publication shows emerging focus on this specific technical challenge
relevance_note: Relevant for AI system testing, validation, and critical system assurance
categories: ["AI safety/alignment", "Model serving/inference", "Other AI/agent"]
rated_at: 2026-03-08T17:22:33.041126+00:00
summary:
  Describes a proxy design process for validation and verification of critical AI systems, addressing the challenge of testing complex and opaque AI systems. Provides practical methodologies for V&V in production AI environments.


draft_name: nist-ir-8579
maturity_note: High maturity based on real implementation experience with concrete security findings
overlap_note: Relatively unique as implementation case study; limited direct overlap with framework documents
momentum_note: Future-dated (2025) indicates ongoing NCCOE LLM security work
relevance_note: Relevant for LLM deployment security, prompt injection mitigation, and practical security guidance
categories: ["AI safety/alignment", "Human-agent interaction", "Model serving/inference"]
rated_at: 2026-03-08T17:22:33.049233+00:00
summary:
  Documents technical and security lessons learned from implementing an LLM-based chatbot at NCCOE, including prompt injection mitigations and practical security considerations. Provides real-world insights from production LLM deployment.

novelty_note:
  Case study approach with practical learnings from actual LLM deployment; good novelty in applied context


draft_name: nist-nist-ai-agent-iam
categories: ["Agent identity/auth", "Policy/governance", "Autonomous netops", "A2A protocols"]
rated_at: 2026-03-08T17:22:40.486551+00:00
summary:
  Concept paper addressing identity and authorization mechanisms for software and AI agents, focusing on authentication, authorization, and accountability in automated systems. Establishes foundational guidance for agent identity management and access control.

novelty_note:
  Highly novel in applying IAM principles specifically to AI agents; addresses emerging need as agents become more autonomous and interconnected.

maturity_note:
  Early-stage concept paper (2026 date suggests forward-looking); limited practical implementations or matured standards yet available.

overlap_note:
  Minimal overlap with measurement/evaluation or RMF governance frameworks; focuses on distinct IAM domain.

momentum_note:
  Strong momentum indicated by NIST initiative and 2026 publication date; reflects industry shift toward agentic AI systems.

relevance_note:
  Critical relevance for multi-agent systems, API security, and autonomous operations; directly addresses authentication/authorization gaps.


draft_name: nist-ai-100-6
momentum_note: Solid momentum as part of active NIST AI 100 series; builds on established AI RMF adoption.
categories: ["Policy/governance", "AI safety/alignment", "Model serving/inference", "Data formats/interop"]
rated_at: 2026-03-08T17:22:40.496568+00:00
summary:
  Guidance document on measurement and evaluation methodologies for assessing AI system trustworthiness across accuracy, fairness, robustness, and security dimensions. Provides structured approaches for AI system assessment.

novelty_note:
  Builds on established evaluation frameworks but applies them comprehensively to trustworthiness; moderate novelty in integration of multiple quality dimensions.

maturity_note:
  Mature guidance from established NIST AI RMF series (2024); based on consolidated industry practices and research.

overlap_note:
  Moderate overlap with RMF Playbook governance structures; complements rather than duplicates measurement guidance.

relevance_note:
  Highly relevant for AI system validation, compliance, and risk management; applicable across diverse AI deployments.


draft_name: nist-ai-100-1-playbook
categories: ["Policy/governance", "AI safety/alignment", "Autonomous netops", "Model serving/inference"]
rated_at: 2026-03-08T17:22:40.504797+00:00
summary:
  Practical playbook companion to the NIST AI RMF providing actionable steps and suggested approaches for implementing governance, mapping, measurement, and management functions. Operationalizes the AI RMF framework.

novelty_note:
  Limited novelty as implementation guide; primarily translates existing RMF concepts into practice rather than introducing new principles.

maturity_note:
  Highly mature guidance from 2023; directly derived from established NIST AI RMF standard with proven adoption.

overlap_note:
  Significant overlap with AI 100-6 on measurement and governance; complementary rather than independent coverage.

momentum_note:
  Very strong momentum as foundational implementation guide; widely referenced in AI governance initiatives.

relevance_note:
  Essential relevance for organizations implementing AI risk management; provides bridge between framework and operational practice.


draft_name: draft-li-rtgwg-distributed-lossless-framework
momentum_note: Limited evidence of community engagement or iterative development in document history.
categories: ["ML traffic mgmt", "Model serving/inference"]
rated_at: 2026-03-08T17:31:23.103679+00:00
summary:
  Proposes a framework for efficient lossless interconnection between multiple data centers to support distributed LLM training at scale. Addresses key technologies for connecting data centers into larger clusters while ensuring reliable data transmission.

novelty_note:
  Distributed data center networking for AI is established; framework contribution is incremental application of existing principles.

maturity_note:
  Early-stage framework lacking detailed protocol specifications, implementation details, or validation results.

overlap_note:
  Overlaps with general distributed systems and data center networking literature; some connection to ML traffic management themes.

relevance_note:
  Relevant to AI infrastructure but narrowly scoped to interconnection layer; may have limited applicability outside large-scale training scenarios.


draft_name: draft-voit-rats-trustworthy-path-routing
categories: ["Agent identity/auth", "Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:31:23.115034+00:00
summary:
  Describes Trusted Path Routing mechanism that forwards sensitive network traffic through devices recently verified as trustworthy using remote attestation. Combines routing decisions with device trustworthiness appraisal to protect confidential data flows.

novelty_note:
  Novel integration of remote attestation (RATS) into routing decisions; represents new approach to security-aware path selection.

maturity_note:
  Mature specification document with clear abstractions; some implementation guidance present but real-world deployment experience unclear.

overlap_note:
  Minimal overlap with other drafts; distinct focus on attestation-aware routing rather than general secure routing.

momentum_note:
  Substantial document length (32pg) and technical depth suggest active development; author (Voit) is known RATS contributor.

relevance_note:
  Highly relevant to emerging security requirements where encryption alone deemed insufficient; applicable to high-sensitivity government and enterprise networks.


draft_name: draft-toorop-dnsop-ranking-dns-data
overlap_note: Highly specialized DNS domain; minimal overlap with other networking or AI-related drafts.
momentum_note: Modest document scope (4pg) suggests focused, bounded contribution; unclear iteration frequency.
relevance_note: Limited relevance to AI systems and distributed agent networks; primarily DNS operational utility.
categories: ["Data formats/interop", "Policy/governance"]
rated_at: 2026-03-08T17:31:23.125418+00:00
summary:
  Extends RFC2181's DNS data trustworthiness ranking by adding entries for root server names, built-in resolver addresses, and DNSSEC-verified data with assigned numeric values. Provides standardized reference framework for comparing DNS data reliability.

novelty_note:
  Incremental extension of established DNS ranking; primarily organizational refinement rather than novel security mechanism.

maturity_note:
  Well-grounded in existing DNS standards (RFC2181); clear operationalization of trustworthiness rankings with practical applicability.


draft_name: draft-sandowicz-httpbis-httpa2
categories: ["Agent identity/auth", "A2A protocols", "Model serving/inference"]
rated_at: 2026-03-08T17:31:23.135383+00:00
summary:
  Extends HTTP with remote attestation capabilities (HTTPA/2) enabling trusted communication via Trusted Execution Environments without requiring TLS. Treats TEE as a requestable resource and allows endpoints to verify each other's trustworthiness through attestation evidence.

novelty_note:
  Novel decoupling of attestation from TLS; interesting approach treating TEE attestation as core protocol feature rather than auxiliary security layer.

maturity_note:
  Detailed specification (34pg) with clear TEE definitions; lacks discussion of standardization status, reference implementations, or deployment considerations.

overlap_note:
  Related to attestation themes in trusted-path-routing draft but distinct protocol layer (HTTP vs routing); complementary rather than overlapping.

momentum_note:
  Substantial technical document suggesting serious effort; unclear whether follow-up versions or community feedback exist.

relevance_note:
  Relevant to agent identity/auth and secure agent communication; applicable to scenarios requiring strong mutual verification of remote execution environments.


draft_name: draft-chen-secure-routing-use-cases
categories: ["Policy/governance", "Autonomous netops"]
rated_at: 2026-03-08T17:31:23.145249+00:00
summary:
  Proposes adding security and trustworthiness factors to routing decisions beyond shortest-path algorithms. Presents use cases for secure routing that converges routing with ISP security infrastructure to ensure secure data transmission.

novelty_note:
  Security-aware routing concept is established; contribution primarily frames use cases rather than novel mechanisms.

maturity_note:
  Early-stage use case document (9pg) lacking detailed protocol design, threat modeling, or implementation validation.

overlap_note:
  Substantial thematic overlap with trusted-path-routing draft; both address security-aware routing but from different angles (use cases vs mechanisms).

momentum_note:
  Short, foundational document suggests early exploration phase; limited evidence of detailed technical development.

relevance_note:
  Moderately relevant to autonomous network operations and security policy integration; applicable to enterprise and ISP scenarios.


