AI governance is the discipline of knowing what AI you run, what risk it carries, and proving you oversee it responsibly. Use this checklist to stand up a credible program.
The checklist
- Inventory every AI/ML system and its purpose.
- Classify risk (e.g. EU AI Act tiers: prohibited, high-risk, limited, minimal).
- Map data each model uses — especially personal and sensitive data.
- Assess bias, explainability and robustness.
- Add human oversight and a release/approval gate.
- Document models, data lineage and decisions (technical documentation).
- Monitor in production and log incidents.
- Keep evidence to demonstrate conformity.
Tie it to privacy
Most AI risk is data risk. Governance works best when it sits on the same discovery, classification and risk backbone as your privacy program.
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