AI Compliance for Compliance Officers
Building and running the actual governance program — inventory, risk tiering, review gates, and the audit trail to prove it's real.
If you're the person accountable for AI compliance day to day, the job isn't writing a policy — it's building a program that survives an actual audit, an actual incident, or an actual regulator inquiry. That means a real systems inventory (including the shadow AI nobody formally approved), a risk-tiering method your organization will actually use under deadline pressure, and a paper trail that proves the review happened rather than just asserting it did.
Start with our governance framework checklist for the build order that tends to hold up, then use the regulation and framework hubs here as your reference material for what "reasonable" looks like in your specific jurisdiction.
Frequently asked questions
- What's the first thing a compliance officer should build for AI governance?
- A real systems inventory — not a policy document. You can't govern AI systems you don't know exist, and shadow AI adopted by individual teams outside formal procurement is the norm, not the exception, at almost every company we've looked at.
- How much documentation does a defensible AI compliance program actually need?
- Enough to hand a regulator, auditor, or enterprise customer's security team three things without scrambling: a current systems inventory with risk tier and named owner, evidence of pre-deployment review for consequential systems, and a record of how the program itself updates when law or internal risk tolerance changes.