Building an AI governance program from scratch

Many organizations are starting AI governance from a blank page. The good news: you don't need to solve everything before you begin. Here's a pragmatic sequence.

1. Assign ownership

Governance fails without an owner. Name an accountable lead and define who is responsible for AI policy, risk and compliance across the organization.

2. Write a lightweight AI policy

Start with a short policy stating principles, acceptable use, and how AI risks are reviewed. You can deepen it later.

3. Pick your frameworks

Most programs anchor on the EU AI Act (if you operate in the EU), ISO/IEC 42001 for a certifiable system, and the NIST AI RMF for day-to-day risk practice. See how they compare.

4. Baseline with a gap analysis

Run an organization-level gap analysis to see where you stand. This turns abstract frameworks into a concrete to-do list.

5. Build the operating rhythm

Stand up recurring risk reviews, evidence collection, and a remediation roadmap you revisit on a cadence. Governance is a system, not a milestone.

The payoff

A program-level foundation means each new framework or regulation becomes an extension of what you already have — not a fresh fire drill.