AI governance fails in two predictable ways: it becomes a checklist that doesn’t change decisions, or it becomes a bureaucratic process that slows delivery. The middle path is a small set of artefacts that make ownership, risk, and evidence visible.
Start with a use-case register, a model inventory, an evaluation evidence pack, a change log, and an incident register. Keep them lightweight, but keep them current.
These artefacts are what make oversight practical (see AI control towers and governance maturity).