Record STMT-W22750FVoluntary

ISO policy brief: Harnessing international standards for responsible AI development and governance

Report Institutional policyGlobaladopted

This ISO policy brief explores the critical role that international standards play in supporting responsible AI development, deployment, and governance across the complete AI lifecycle. It examines the global policy context, highlights both the opportunities and risks associated with artificial intelligence, and advocates for a socio-technical approach to standards development. Finally, the brief provides concrete recommendations for policymakers, standards bodies, industry stakeholders, and civil society to foster trust, interoperability, and ethical alignment.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

International Organization for StandardizationStandards body

Lead issuer

Legal forceVoluntary

Under whose authorityInstitutional policy

Judged fromfull text

Who it governs

National governmentRegulatorsCompaniesAI developers and providersAI deployers and usersResearchers and academics

Policymakers, standards bodies, industry stakeholders, and civil society actors seeking guidance on how to leverage international standards for responsible AI governance.

Sectors

Cross-sectorResearch and science · artificial intelligence research and standardization

What the document contains

What's covered

This policy brief covers the role of international standards across the full lifecycle of artificial intelligence systems. It addresses how standards help mitigate technical risks, improve data quality, promote ethical alignment, support sustainability, and enable compliance through conformity assessment.

What's missing

The document does not establish legally binding laws, punitive enforcement mechanisms, or direct judicial remedies; instead, it serves as an informational policy and guidance resource.

Key takeaways

International standards establish a common technical foundation and consensus-built definitions that accelerate trustworthy AI innovation and global trade.
A socio-technical approach is essential for AI governance because AI systems interact continuously with people, organizations, and broader social and economic contexts.
International standards translate high-level ethical principles into concrete, actionable technical steps and risk management frameworks.
Conformity assessment, underpinned by international standards, enables robust verification of AI compliance with policies, regulations, and technical requirements.
Incoroporating diverse multi-stakeholder participation in standards development ensures that standards effectively respond to both technical realities and societal needs.

Principles it states

SafetyReliabilityTransparencyAccountabilityFairnessSustainability

Outline

· Executive summary
· Glossary of abbreviations
· 1. Introduction
· 2. AI Governance is a global challenge
  - 2.1 What is AI?
  - 2.2 Opportunities of AI
  - 2.3 AI risks
  - 2.4 The role of standards in socio-technical AI governance
· 3. Policy context
  - 3.1 Selected international initiatives
  - 3.2 Selected regional frameworks
  - 3.3 National approaches
· 4. Standards in support of AI policy
  - 4.1 Ensuring quality, safety, and reliability
  - 4.2 Improve data quality and establish data governance
  - 4.3 Promoting good governance and ethical alignment
  - 4.4 Advancing innovation and economic growth
  - 4.5 Advancing sustainability
  - 4.6 Supporting policy, regulation and compliance
  - 4.7 Supporting responsible applications of AI
· 5. Key messages
· 6. Recommendations
  - 6.1 For policymakers
  - 6.2 For standards bodies
  - 6.3 For industry stakeholders
  - 6.4 For civil society
· 7. How can I get involved?
  - 7.1 NSBs
  - 7.2 Stakeholders
· 8. References

Issued2025

Length12,481 words · 44 pages

FormatNot recorded

Scopeglobal

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

4/5

Clear responsibility for AI outcomes

The ISO/IEC 38505 series, Governance of data, establishes principles for data governance and accountability, including those relevant to AI systems.

Section 4.2

screening score · 2026-10-24

Fairness

4/5

Non-discrimination and equitable treatment

ISO/IEC TR 24027:2021, Bias in AI systems and AI aided decision making, describes measurement techniques and methods for assessing bias in AI systems.

Section 4.1

screening score · 2026-10-24

Human Dignity

2/5

Respect for the inherent worth of persons

At the same time, it presents complex challenges spanning from bias, intellectual property, and privacy to effective human oversight and organizational risk management.

Executive summary

screening score · 2026-10-24

Human Oversight

4/5

Humans remain in control of consequential decisions

ISO/IEC TS 8200:2024, AI – Controllability of automated artificial intelligence systems, specifies a framework with principles, characteristics and approaches to improve AI systems’ controllability

Section 4.1

screening score · 2026-10-24

Privacy

4/5

Protection of personal data and private life

ISO/IEC 29100:2024, Security techniques – Privacy framework, defines a privacy framework for personal privacy protection, essential for complying with data privacy laws when AI systems process personal information.

Section 4.2

screening score · 2026-10-24

Transparency

4/5

Openness about how AI systems work and are used

ISO/IEC 12792:2025, Information technology – AI – Transparency taxonomy of AI systems, defines a taxonomy to assist stakeholders with identifying and addressing the needs for transparency of AI systems.

Section 4.3

screening score · 2026-10-24

Enforcement

2/5

Consequences and compliance mechanisms with real force

Conformity assessment, underpinned by international standards, enables robust verification of AI systems' compliance with policies, regulations and technical standards

Section 5

screening score · 2026-10-24

Impact Assessment

4/5

Required assessment of an AI system's risks/impacts before or during use

ISO/IEC 42005:2025, AI system impact assessment, provides organizations a framework to understand how AI systems may affect individuals, groups or society at large across the AI system lifecycle.

Section 4.3

screening score · 2026-10-24

Topics

artificial_intelligence international_standards ai_governance conformity_assessment sociotechnical_approach