Regulations/EU AI Act/AI Governance
AI Governance · EU AI Act

AI Governance for EU AI Act.

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: Regulation (EU) 2024/1689Use: evidence-readinessBoundary: not legal advice
EU AI Act TRACE ARTICLE 3 DEFINITIARTICLE 4 AI LITARTICLE 5 PROHIBARTICLE 6 AND AN
/ AI governance

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

EU AI Act
Control 01

Inventory control

Every AI system needs owner, intended use, data source, actor role, and risk hypothesis.

Control 02

Literacy evidence

Training maps to role, technical knowledge, use context, and affected persons.

Control 03

Human oversight

Oversight has to be designed into workflow, not written as a principle only.

Control 04

Monitoring

Performance and incident learning feed post-market or operational review.

/ Adjacent controls

AI governance must connect to existing regulated systems.

not isolated
Evidence 01

AI system inventory with intended use and owner

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

Evidence 02

Actor-role decision record

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

Evidence 03

Risk classification rationale

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

Evidence 04

AI literacy training map by role

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

Evidence 05

Human oversight description

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

Evidence 06

Technical documentation index

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