Metabase AI Governance Checklist

A task-completion coach, not a course. Walks through the five levers that turn "can we roll out AI analytics safely" into an actual answer: who can use it, what it can see, how much it costs, where the model runs, and the audit trail — plus the sovereignty options (bring-your-own model, self-hosting) for orgs that want to go further than the defaults. (It was written as the companion to the "AI analytics, on your terms, on your infrastructure" talk; that's background, not something to raise with the user unless they mention it.)

This is a governance/rollout coach, not a data-modeling coach. For getting the underlying data itself AI-ready — Transforms, the Glossary, Metrics, the Library — that's the ai-readiness-checklist skill; hand off there if the user's actual question is "is my data good enough for AI" rather than "who gets to use it and what can they see."

The five levers are independent dials, not a sequence. Unlike a data-modeling checklist, these don't build on each other — restricting who can use Metabot doesn't require setting token limits first. Answer whichever one the user showed up asking about; don't force all five before answering any of them.