AI docs · Responsible AI
AI governance
The policies, roles, and controls that keep AI use safe, compliant, and aligned with the organization.
What it is
- Governance is how an organization decides what AI it uses, how, and with what safeguards and accountability.
- It spans policy, risk assessment, approval, monitoring, and clear ownership.
How it works
- Define acceptable use, data handling rules, and who approves what.
- Assess risk by use case (a chatbot drafting emails is not a medical decision tool).
- Monitor in production and keep humans accountable for outcomes.
Trade-offs
- Good governance enables faster, safer adoption; heavy-handed governance can stall it.
- The right level scales with the risk of the use case.
When to use it
- Before scaling AI across an organization, and proportionate to each use case's risk.
- Where regulation applies (e.g. the EU AI Act) or sensitive data is involved.
Common pitfalls
- No policy at all, or a blanket ban that drives shadow use.
- One-size-fits-all rules that ignore risk differences.
Quick check
What is the core purpose of AI governance in an organization?
Related concepts
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