AI Glossary
AI governance
AI oversight, AI governance
AI governance is the set of rules, roles, and processes that determine how an organization deploys and controls AI systems. It covers accountability, permitted uses, risk assessment, and the requirement for oversight.
- It defines who owns a system, which uses are allowed, and where human sign-off is required.
- It pulls legal requirements, risk, and internal policy together into one coherent set of rules.
- It runs from design, through deployment, to retirement of a model — not just at launch.
AI governance is how an organization stays in control of its AI systems. It sets out who owns a given model, what it may be used for, how risk is measured, and when a decision must be approved by a person. It turns broad intentions into concrete rules and control points.
Governance spans the full lifecycle of a system: from the decision to build, through testing and deployment, to monitoring and retirement. It rests on other mechanisms. Guardrails and a human in the loop enforce the rules in operation, while an AI audit checks whether they are actually being followed.
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