AI governance is the set of policies, controls, and structures that determine how AI systems are deployed, monitored, and held accountable inside an organization. It covers what AI is allowed to do, who can authorize new uses, how outcomes are audited, and how systems are retired or revoked.
AI governance is distinct from AI safety and from AI alignment. Safety asks whether AI systems can be made reliable in principle. Alignment asks whether their goals match human intent. Governance asks how an organization actually exercises authority over AI in its day-to-day operation.
Good AI governance is not a document. It is operational infrastructure — visible in the gates around AI deployment, the audit logs of AI action, and the named owners of every AI scope.
Why AI governance Matters for Distributed Teams
AI governance is the discipline that determines whether an organization adopts AI as a force multiplier or as an accountability sink. The same technology produces different outcomes depending on the governance layer around it.
Frequently Asked Questions
What is AI governance?
AI governance is the set of policies, controls, and structures that determine how AI systems are deployed, monitored, and held accountable inside an organization. It covers allowed uses, authorization paths, audit requirements, and revocation procedures.
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