EU AI Act Guide

EU AI Act data governance

Data governance under EU AI Act readiness is about knowing which data enters the system, how quality and relevance are controlled, where sensitive data appears and what evidence the company can show.

Run the diagnostic first

Operational information, not legal advice.

Obligation evidence map

EU AI Act Data Governance

01

Obligation

Identify which obligation, control area or governance requirement is triggered.

02

Evidence

Define which document, record, process proof or artifact must support the claim.

03

Owner

Assign the team or role responsible for keeping the evidence current.

04

Review point

Set the point where evidence must be reviewed before implementation continues.

Strategic answer

Data governance is a readiness question before it is a documentation task.

EU AI Act readiness requires teams to understand what data enters the system, how it is controlled, whether it is relevant to the use case and whether sensitive data creates additional exposure. This should be mapped before generic governance documents are written.

Start with the EU AI Act Diagnostic, turn findings into an implementation plan, and see how the diagnostic works as a reference app on M13.

Exposure focus

What data governance should clarify

  • Input data, training data, operational data and output dependency.
  • Data quality, relevance, representativeness and review practices.
  • Sensitive data exposure in employment, education, healthcare or finance workflows.
  • Evidence that data controls are active, owned and reviewable.

First action

What to do first

  1. 01Map data sources per AI system.
  2. 02Identify sensitive or decision-relevant data flows.
  3. 03Document quality checks and review ownership.
  4. 04Connect data gaps to the implementation plan.

This page provides operational information for AI governance readiness. It is not legal advice.

Related guides

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EU AI Act Risk Assessment

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