AI Governance · ISO/IEC 42001

AI Governance for ISO/IEC 42001.

This page focuses on AI governance implications inside regulated work. It shows where AI changes evidence needs while keeping quality, regulatory, data, supplier, and human accountability controls in view.

Source basis: ISO/IEC 42001 Artificial intelligence management systemUse: evidence-readinessBoundary: not legal advice
ISO/IEC 42001 TRACE ISO/IEC 42001 SOURISO EXPLAINERIEC LISTINGAIMS SCOPE
/ AI governance

AI changes the evidence pattern, not the need for control.

ISO/IEC 42001
Control 01

Management-system scope

Define which AI activities, teams, products, and suppliers are inside the AIMS.

Control 02

Risk and impact

AI risks and impacts need owners, controls, and review cycles.

Control 03

Supplier AI

External models and platforms need due diligence and monitoring.

Control 04

Continual improvement

Incidents, findings, and changes feed management review and action closure.

/ Adjacent controls

AI governance must connect to existing regulated systems.

not isolated
Evidence 01

AI management-system scope

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 02

AI policy

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 03

AI objectives

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 04

Role and responsibility matrix

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 05

AI risk register

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 06

AI system inventory

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.