Comprehensive reference for AI-related technical standards from ISO/IEC, IEEE, NIST, and other standards bodies — covering management systems, risk frameworks, safety, transparency, and trustworthiness.
Last updated: February 2026 10 Sections Standards Bodies
Technical standards translate high-level AI governance principles into concrete, implementable requirements. They are increasingly referenced in legislation (the EU AI Act explicitly references harmonised standards) and serve as the practical bridge between policy intent and engineering practice.
Key Standards Bodies
Organization
Type
AI Standards Scope
Website
ISO/IEC JTC 1/SC 42
International
Foundational AI standards; management systems; trustworthiness; data quality
ISO/IEC 42001:2023 is the world’s first international standard for AI management systems. Published December 2023, it provides a certifiable framework for organizations developing, providing, or using AI systems. It follows the Annex SL structure familiar from ISO 9001 and ISO 27001.
2.1 Structure
Clause
Title
Key Requirements
4
Context of the Organization
Understanding the organization, interested parties, scope, and AIMS
5
Leadership
Management commitment; AI policy; roles and responsibilities
6
Planning
Risk assessment; AI impact assessment; objectives and plans
7
Support
Resources; competence; awareness; communication; documented information
8
Operation
AI system lifecycle processes; data management; third-party considerations
Annex A provides 38 controls across 8 domains; Annex B provides implementation guidance. The controls cover AI policy, responsible AI, impact assessment, AI system lifecycle, data for AI, information for interested parties, use of AI systems, and third-party relationships.
3. NIST AI Risk Management Framework (AI RMF 1.0)
3.1 Background
Published January 2023, the NIST AI RMF is a voluntary framework designed to help organizations manage risks associated with AI systems. Referenced by the US Executive Order on AI (EO 14110) and widely adopted internationally.
3.2 Core Structure
Function
Description
Key Categories
GOVERN
Cultivate a culture of risk management; establish policies, processes, procedures
AI RMF Playbook: Practical guidance with suggested actions for each subcategory
AI RMF Generative AI Profile (2024): Extends the framework specifically for generative AI risks including hallucination, CBRN, CSAM, and dual-use concerns
Crosswalks: Mappings between AI RMF and ISO 42001, EU AI Act, OECD principles
4. IEEE AI Standards
4.1 P7000 Series (Ethically Aligned Design)
Standard
Title
Status
Scope
IEEE 7000-2021
Model Process for Addressing Ethical Concerns During System Design
Published
Ethical value-based design process for any system
IEEE 7001-2021
Transparency of Autonomous Systems
Published
Measurable transparency levels for autonomous systems
IEEE 7002-2022
Data Privacy Process
Published
Privacy engineering for AI and autonomous systems
IEEE 7003-2023
Algorithmic Bias Considerations
Published
Bias detection and mitigation across AI lifecycle
IEEE P7004
Child and Student Data Governance
In development
Protecting minors’ data in AI systems
IEEE P7005
Employer Data Governance
In development
Workplace data governance for AI
IEEE P7006
Personal Data AI Agent
In development
Standards for AI agents managing personal data
IEEE P7007
Ontological Standard for Ethically Driven Robotics and Automation Systems
In development
Ontology for ethical robotics
IEEE P7008
Ethically Driven Nudging for Robotic, Intelligent, and Autonomous Systems
In development
Ethical persuasion in AI systems
IEEE P7009
Fail-Safe Design of Autonomous and Semi-Autonomous Systems
In development
Fail-safe engineering for AI
IEEE P7010
Wellbeing Metrics Standard for Ethical AI and Autonomous Systems
In development
Measuring human wellbeing impact
5. Other ISO/IEC AI Standards
Standard
Title
Year
Key Content
ISO/IEC 22989
AI Concepts and Terminology
2022
Foundational definitions; taxonomy of AI concepts
ISO/IEC 23053
Framework for AI Systems Using ML
2022
Reference architecture for ML-based AI systems
ISO/IEC 23894
AI Risk Management
2023
Risk management guidance specific to AI systems
ISO/IEC 38507
Governance Implications of AI
2022
Board-level governance guidance for AI
ISO/IEC 25059
Quality Model for AI Systems
2023
Quality characteristics specific to AI (extends SQuaRE)
ISO/IEC TR 24027
Bias in AI Systems
2021
Sources of bias; measurement approaches; mitigation
ISO/IEC TR 24028
Trustworthiness in AI
2020
Overview of trustworthiness concerns and approaches
ISO/IEC TR 24029
Assessment of Neural Network Robustness
2021
Methods for evaluating robustness of neural networks
ISO/IEC TR 24030
AI Use Cases
2021
Collection of AI use cases across sectors
ISO/IEC 5259 series
Data Quality for AI
2024
Multi-part standard on AI training/test data quality
ISO/IEC 12792
Transparency Taxonomy
2024
Taxonomy of AI transparency concepts and requirements
6. AI Safety Standards
6.1 Emerging Safety Standards
Standard/Framework
Organization
Focus
Status
ISO/IEC DIS 27090
ISO/IEC
Cybersecurity for AI
Draft
ISO/IEC DIS 27091
ISO/IEC
Privacy protection for AI
Draft
ETSI SAI GR 004
ETSI
Problem statement on securing AI
Published
ETSI SAI GR 005
ETSI
Mitigation strategy for AI threats
Published
NIST AI 100-2e2025
NIST
Adversarial ML — Taxonomy and terminology
Published
NIST AI 600-1
NIST
Generative AI Profile (AI RMF companion)
Published
UL 4600
Underwriters Laboratories
Safety for autonomous products (vehicles, drones, robots)
Published
7. Sector-Specific Standards
Sector
Standard
Scope
Healthcare
IEC 62304 (medical device software); ISO 14971 (risk management); IEC 82304-1 (health software); WHO AI ethics guidance
Medical AI device lifecycle; clinical validation; patient safety
Automotive
ISO 26262 (functional safety); ISO/PAS 21448 (SOTIF); SAE J3016 (driving automation levels); UL 4600
SR 11-7 (OCC model risk management); SS1/23 (PRA/BoE model risk); IEEE 2863 (org governance of ML)
Model validation; explainability; fair lending; anti-money laundering
Aerospace
EASA AI Concept Paper; SAE AIR6988; EUROCAE ED-324
AI in aviation systems; certification; operational approval
8. Standards & Regulatory Compliance
8.1 EU AI Act Harmonised Standards
The EU AI Act relies on harmonised standards developed by CEN/CENELEC to operationalize its requirements. CEN/CENELEC JTC 21 has been tasked with developing standards that, when followed, create a presumption of conformity with the AI Act.