Executive AI Governance Review Checklist

A quarterly AI governance review package

Prepare the current use-case register, material risks, incidents, unresolved control failures, provider changes, adoption evidence, and decisions requiring executive attention. Reconcile the register with actual systems in use and assign owners for gaps.

The governance kit supplies the operating records. For AI-assisted quality checking of executive papers, use the board-pack review guide. For a hiring workflow, add the recruiting governance checklist.

A useful board review explains the limits of the evidence. Demonstrations, self-assessment scores, and planned controls should not be presented as verified operating outcomes.

Purpose

This checklist supports quarterly or board-level review of AI Governance maturity. It is designed for oversight conversations that ask whether controls are operating, improving, and matched to the organization's AI footprint.

Who Should Complete It

• Executive sponsor or risk committee lead
• AI governance chair or equivalent
• Legal, compliance, and security leads
• CIO or technology risk lead
• Business representatives for material AI systems

Prepare evidence before the review meeting. The checklist is most effective when used as a management pack, not as an improvisation exercise.

Instructions

For each item select Yes, No, In Progress, or Not Applicable. Focus on operating effectiveness since the last review period. Note material changes in inventory, incidents, vendors, and regulations.

Scoring Guidance

• Yes = 2
• In Progress = 1
• No = 0
• Not Applicable = exclude

Track trend versus prior quarter. A stable moderate score with improving critical controls can be healthier than a high score without evidence.

Assessment Questions

Policy Maturity

1. AI policy is approved and current. (Yes / No / In Progress / N/A)
2. Supporting standards exist for high-risk use. (Yes / No / In Progress / N/A)
3. Policy exceptions are controlled and time-bound. (Yes / No / In Progress / N/A)
4. Employees can access practical policy guidance. (Yes / No / In Progress / N/A)
5. Policy updates followed material technology or legal changes. (Yes / No / In Progress / N/A)
6. Training coverage for policy obligations is measured. (Yes / No / In Progress / N/A)

Oversight and Decision Making

7. Governance forum met according to schedule. (Yes / No / In Progress / N/A)
8. Decision rights remain clear and contested cases are resolved. (Yes / No / In Progress / N/A)
9. Material use cases received proportionate review. (Yes / No / In Progress / N/A)
10. Pause or rollback authority was exercisable when needed. (Yes / No / In Progress / N/A)
11. Minutes or decision logs exist for material approvals. (Yes / No / In Progress / N/A)
12. Escalations to executive or board level occurred when warranted. (Yes / No / In Progress / N/A)

Ethics and Responsible Use

13. Sensitive use cases receive ethical or impact review. (Yes / No / In Progress / N/A)
14. Human oversight requirements are enforced in practice. (Yes / No / In Progress / N/A)
15. Customer or citizen transparency needs are addressed. (Yes / No / In Progress / N/A)
16. Fairness concerns are investigated and documented. (Yes / No / In Progress / N/A)
17. Prohibited use violations are tracked and addressed. (Yes / No / In Progress / N/A)
18. Responsible use metrics appear in leadership reporting. (Yes / No / In Progress / N/A)

Compliance and Regulatory Readiness

19. Applicable AI-related obligations are mapped. (Yes / No / In Progress / N/A)
20. Regulatory change monitoring is active. (Yes / No / In Progress / N/A)
21. Evidence can be produced for priority systems. (Yes / No / In Progress / N/A)
22. Privacy obligations for AI processing are met. (Yes / No / In Progress / N/A)
23. Sector-specific requirements are reflected in controls. (Yes / No / In Progress / N/A)
24. External inquiries can be answered with named owners. (Yes / No / In Progress / N/A)

Risk Management

25. AI risk register is current. (Yes / No / In Progress / N/A)
26. Top risks have owners and mitigations. (Yes / No / In Progress / N/A)
27. Residual risk acceptances are authorized. (Yes / No / In Progress / N/A)
28. New high-risk use cases were assessed before scale. (Yes / No / In Progress / N/A)
29. Concentration risk across critical AI systems is reviewed. (Yes / No / In Progress / N/A)
30. Emerging risks are discussed prospectively, not only after incidents. (Yes / No / In Progress / N/A)

Vendor Governance

31. Material AI vendors are inventoried. (Yes / No / In Progress / N/A)
32. Due diligence standards were applied to new vendors. (Yes / No / In Progress / N/A)
33. Contractual control terms are adequate for risk tier. (Yes / No / In Progress / N/A)
34. Vendor performance and incidents are reviewed. (Yes / No / In Progress / N/A)
35. Fourth-party or model-provider dependencies are visible. (Yes / No / In Progress / N/A)
36. Exit readiness for critical vendors is understood. (Yes / No / In Progress / N/A)

Performance Monitoring

37. Production systems have monitoring for quality and misuse. (Yes / No / In Progress / N/A)
38. Override and escalation trends are reviewed. (Yes / No / In Progress / N/A)
39. Value metrics are reviewed alongside risk metrics. (Yes / No / In Progress / N/A)
40. Drift or degradation triggers investigation. (Yes / No / In Progress / N/A)
41. Underperforming systems are remediated or retired. (Yes / No / In Progress / N/A)
42. Executive dashboards include governance health indicators. (Yes / No / In Progress / N/A)

Auditability and Documentation

43. AI inventory completeness is acceptable. (Yes / No / In Progress / N/A)
44. Ownership records are accurate. (Yes / No / In Progress / N/A)
45. Key system documentation is current. (Yes / No / In Progress / N/A)
46. Approval and change records are retrievable. (Yes / No / In Progress / N/A)
47. Incident records are complete enough for learning. (Yes / No / In Progress / N/A)
48. Audit findings related to AI are tracked to closure. (Yes / No / In Progress / N/A)

Operating Model and Capacity

49. Governance roles are staffed adequately. (Yes / No / In Progress / N/A)
50. Intake volume is manageable without unsafe shortcuts. (Yes / No / In Progress / N/A)
51. Business units follow standards rather than bypassing them. (Yes / No / In Progress / N/A)
52. Shadow AI risk is measured and reducing for high-risk use. (Yes / No / In Progress / N/A)
53. Training completion and quality are reviewed. (Yes / No / In Progress / N/A)
54. Funding for governance operations is sustained. (Yes / No / In Progress / N/A)

Continuous Improvement

55. Lessons from incidents inform control updates. (Yes / No / In Progress / N/A)
56. Policy and process changes have owners and dates. (Yes / No / In Progress / N/A)
57. Benchmarks or external frameworks are used thoughtfully. (Yes / No / In Progress / N/A)
58. Prior quarter actions were completed or re-baselined. (Yes / No / In Progress / N/A)
59. Governance maturity trend is reviewed by executives. (Yes / No / In Progress / N/A)
60. Roadmap investments reflect governance gaps. (Yes / No / In Progress / N/A)

Board and Executive Assurance

61. Board or committee questions can be answered with evidence. (Yes / No / In Progress / N/A)
62. Material AI risks are disclosed at the right altitude. (Yes / No / In Progress / N/A)
63. No known critical control failure remains unescalated. (Yes / No / In Progress / N/A)
64. Assurance activities for the next quarter are planned. (Yes / No / In Progress / N/A)
65. Cross-functional accountability is visible in outcomes, not only charters. (Yes / No / In Progress / N/A)
66. Strategy and governance remain aligned as the portfolio grows. (Yes / No / In Progress / N/A)
67. High-autonomy systems receive heightened oversight attention. (Yes / No / In Progress / N/A)
68. The organization can demonstrate control improvement over time. (Yes / No / In Progress / N/A)

Interpretation of Results

High maturity (about 80%+): Governance is operating as an enterprise capability. Focus on trend monitoring, regulatory anticipation, and selective deep dives.

Moderate maturity (50% to 79%): Maintain selective growth. Prioritize closure of oversight, inventory, vendor, and evidence gaps before expanding high-impact AI.

Low maturity (below 50%): Governance is not keeping pace with adoption. Slow expansion, strengthen fundamentals, and increase executive attention immediately.

Compare scores to the previous quarter. Declining inventory completeness or rising unmanaged exceptions are early warning signs even when overall scores appear stable.

Recommended Next Actions

1. Produce a one-page executive summary of scores, trends, and top risks.
2. Assign owners to every critical "No" and overdue action.
3. Adjust the AI portfolio and roadmap where governance capacity is insufficient.
4. Schedule targeted deep dives for the weakest sections.
5. Repeat this review on a quarterly cadence.

Frequently Asked Questions

Is this checklist sufficient for regulatory examination?

It supports oversight readiness but does not replace formal audits, legal advice, or jurisdiction-specific assessments.

How detailed should evidence be for board use?

Enough to substantiate claims and identify gaps. Boards need assurance and trend clarity, not raw operational noise.

What if our AI footprint is still small?

Use the checklist to ensure controls grow with adoption. Early discipline is easier than remediation after uncontrolled expansion.

Summary

This executive governance review checklist provides a board-level view of policy maturity, oversight, ethics, compliance, risk management, vendor governance, monitoring, auditability, and continuous improvement. Used quarterly with evidence, it helps leaders keep AI adoption aligned with accountability and organizational readiness.