AI system context
Scope should reflect whether the organization develops, provides or uses AI, plus the lifecycle stages and interested parties it can control or influence.
AI governance
Build an AI management system that connects AI systems and impacts to accountable decisions, controls, monitoring and improvement.
Current edition
The first edition was published in December 2023. It specifies requirements for establishing, implementing, maintaining and continually improving an AI management system.
Scope should reflect whether the organization develops, provides or uses AI, plus the lifecycle stages and interested parties it can control or influence.
Governance needs to address AI-specific risks, opportunities and impacts rather than treating information-security risk as a substitute.
Policies, roles, data, lifecycle controls, monitoring, audit and management review need traceable implementation and operating evidence.
Use the official ISO overview to confirm the edition and obtain the standard through an authorized source for exact requirements.
Practical resources
Original guidance for AIMS boundaries, integration and evidence-based AI governance.
Guide
Integrate ISO 42001 and ISO 27001 through shared governance, linked risks and coordinated evidence while preserving distinct AIMS and ISMS conclusions.
Comparison
Compare ISO 42001 and ISO 27001 scope, risks, controls and audit evidence so AIMS and ISMS responsibilities remain clear without governance gaps.
Guide
Use AI in ISO 27001 consulting with approved data boundaries, human validation, traceable sources, client ownership and evidence-focused quality controls.