Answers to recurring questions about ISO/IEC 42001 scope, AI policy, risk and impact assessment, Annex controls, monitoring, roles, certification, and the relationship with legal requirements.
ISO/IEC 42001 is a voluntary, certifiable management-system standard. It can organise AI governance but does not certify a model or replace applicable law, contracts, sector rules, or customer requirements.
Structured answer sets in this page tree.
Cited legal and guidance references.
Start with the boundary and the organisation's role in developing, providing, or using AI systems. The answers below distinguish management-system requirements from optional implementation choices and from separate legal classifications such as the EU AI Act's provider, deployer, or high-risk categories.
These focused FAQ modules break this artifact into narrower answer sets so teams can move straight to the right source-backed guidance.
ISO/IEC 42001 AI policy requirements, approval, communication, evidence, alignment with other policies, and review triggers.
ISO/IEC 42001 certification scope, readiness evidence, internal audit, management review, corrective action, and claim limits.
Apply ISO/IEC 42001 to generative AI development, procurement, integration, employee use, supplier evidence, impacts, controls, and monitoring.
Separate ISO/IEC 42001 organisational risk criteria from legal high-risk AI classifications, with evidence, approval, and reassessment triggers.
Design and evidence effective human oversight under ISO/IEC 42001, including competence, information, intervention authority, testing, and review.
Distinguish ISO/IEC 42001 operational monitoring from legal post-market monitoring and connect real-world evidence to risk, review, incidents, and correction.
Map ISO/IEC 42001 lifecycle responsibilities across developers, users, suppliers, customers, and third parties while keeping legal operator roles separate.
Select, justify, approve, operate, and review ISO/IEC 42001 risk controls, including Annex A comparison, the statement of applicability, residual risk, and evidence.
The standard specifies requirements for establishing, implementing, maintaining, and continually improving an . Its Clauses 4-10 cover context, leadership, planning, support, operation, performance evaluation, and improvement.
A conformity claim or certificate relates to the defined scope and audit criteria. It does not by itself prove that a particular model is accurate, unbiased, safe, lawful, or compliant with the EU AI Act or another regulation.
No. The organisation determines necessary controls through AI risk treatment, compares them with Annex A to check that necessary controls were not omitted, considers relevant Annex A controls and Annex B guidance, and identifies additional controls where needed.
Document the rationale for selected, excluded, different, and additional controls. The resulting set should address the organisation's objectives, risks, AI activities, interested-party requirements, and context.
AI risk assessment applies the organisation's risk criteria to identify, analyse, and evaluate AI risks. AI-system impact assessment examines potential consequences of deployment, intended use, and foreseeable misuse for individuals, groups, and societies in the relevant context.
The impact-assessment result informs the AI risk assessment. It should be performed at planned intervals or when significant changes are proposed, and its results should be retained. Discipline-specific privacy, safety, security, or legal assessments can still be necessary.
Annex A.10 addresses allocation of responsibilities across the AI-system lifecycle, supplier alignment with the organisation's responsible AI approach, and consideration of customer expectations and needs.
Contracts can support that allocation, but the still needs operational evidence: accepted responsibilities, information exchange, service and model changes, incident routes, monitoring data, limitations, and escalation or exit arrangements.
Monitor and evaluate performance and control effectiveness, run an internal audit programme, conduct management reviews, address nonconformities and their causes, and verify corrective-action effectiveness.
Also trigger review when the boundary, organisational context, interested-party requirements, AI purpose, data, supplier, customer allocation, deployment context, risk, impact, or relevant law changes.
Capture owners, evidence, decisions, and review dates in one workflow record so AI governance controls and escalation points stay auditable over time.
Convert ISO/IEC 42001 FAQ into accountable tasks, evidence requests, and review checkpoints.
Review your current scope, evidence gaps, and next implementation steps.
"requirements for establishing, implementing, maintaining and continually improving an Artificial Intelligence Management System"