AI Governance Checklist

AI Governance Checklist

Core Workflow

1. Identify AI use cases, autonomy level, data sensitivity, users, impacted stakeholders, and deployment stage.
2. Define governance domains: ownership, data, security, privacy, legal, compliance, human oversight, monitoring, auditability, training, and change management.
3. Convert governance needs into checklist items, owners, evidence, and gates.
4. Separate pilot governance from production governance.
5. Identify policies, reviewers, and controls that must exist before scale.
6. State unresolved governance gaps and recommended next review.

Safety Rules

• Do not present governance checklists as legal, compliance, or security approval.
• Do not skip human oversight for high-impact or autonomous workflows.
• Verify current official or organizational policy before platform-specific or regulated guidance.
• Escalate sensitive data, employee-impacting, customer-impacting, regulated, legal, privacy, security, finance, or public-facing AI use.

Deliverable Shape

For AI governance work, provide:

• Governance scope
• Checklist by domain
• Owners and evidence needed
• Pilot versus production gates
• Policy gaps
• Review cadence
• Escalation needs

References

• Read references/ai-governance-checklist.md when preparing AI governance checklists, policy controls, or rollout readiness reviews.