AI Delivery Governance Checklist for Product Teams

Successful AI programs are rarely blocked by model quality alone. Governance gaps create the largest delivery risks.

1. Define ownership. Assign accountable owners for data, model behavior, and user-facing outcomes.
2. Establish review gates. Require architecture, security, and quality approvals at each phase.
3. Track evidence. Preserve evaluation snapshots, test logs, and deployment notes for auditability.
4. Control rollout risk. Use staged releases with feature flags and monitoring for regressions.
5. Close the feedback loop. Feed support signals and product metrics into the next iteration cycle.

This governance checklist helps teams ship confidently while preserving speed and transparency.