The CEO’s Guide to AI Governance

Executive Summary: If your AI governance lives in a legal appendix, you’re already exposed. AI governance is now a board-level discipline, on par with financial controls. Here’s the minimum viable policy every CEO needs before scaling AI.

The Shift

Three years ago, “AI governance” was a line item in a legal review. Today it’s a board topic — because the risk surface is real, the regulators are moving, and a single AI failure can be a brand event.

The Five Policy Domains

A defensible AI governance policy covers five domains. Each is one policy, with one owner, reviewed annually.

  1. Data — What data can we use to train, fine-tune, or prompt? Who owns it? What’s the consent posture?
  2. Model — Which models are approved for which use cases? How do we evaluate them? When is human-in-the-loop mandatory?
  3. Vendor — What does every AI vendor contract require? Liability, training opt-out, audit rights, exit clauses.
  4. Disclosure — When do we tell customers, employees, and regulators that AI is in the loop? What about synthetic content?
  5. Risk — What’s our risk register? How do we triage incidents? Who can pull the kill switch?

The 30-Day Sprint

The minimum viable governance policy can be drafted in 30 days with the right team. The output is a 5-page document, approved by the executive committee, that answers the five questions above with one paragraph each.

This is not a binder. It’s a working document — and the working version matters more than the polished one.

What The Board Asks

In our board-readiness work, we see four questions consistently:

  • What is our AI risk register, and what’s the top item?
  • Who can authorize a new AI vendor?
  • When did we last review our top-5 AI use cases for bias and drift?
  • What is our disclosure policy for AI-generated content?

If the CEO can’t answer all four in two minutes, the governance is not yet a discipline. It’s a paragraph in a vendor contract.