AI governance

AI governance is the set of controls determining who may use which AI capabilities, on what data, with what oversight, and with what record. Governance is effective only when enforced by infrastructure: a policy requiring review means nothing if the tooling does not make review mandatory and traceable.

The common failure is documented governance that is not enforced. Organizations write the policy, satisfy the audit question, and leave the behavior unchanged because nothing in the system requires it.

Governance that survives contact with real workloads is proportionate. Requiring human review of every decision creates a bottleneck teams route around, and a bypassed control provides worse assurance than a lighter one that people actually follow.