AI governance

AI governance is the set of policies, controls, and accountabilities that determine how an organisation builds, buys, and uses AI: which systems are approved, what data they may use, who is answerable for outcomes, and how use is evidenced.

It covers four questions in practice. Which AI systems are permitted, what data each may process, which decisions require a human, and how all of that is evidenced to an auditor or regulator after the fact.

Most programmes begin as policy documents and stall there, because a policy that is not enforced by the systems people actually use is a statement of intent. The shift that makes governance real is moving controls from the document into the path of the work.

Governance is often framed as a brake on adoption. In practice it is usually the opposite: teams that can show what an assistant may touch and who approved it get to deploy it, and teams that cannot stay stuck in pilots.