AI governance works best as an operating process, not a one-time approval. A recurring review brings owners together to check whether use cases still match their approved purpose, controls are operating, important changes have been assessed, and open issues have a clear path to resolution.
Review the current inventory
Start with active, pilot, paused, and recently changed use cases. Confirm the owner, purpose, users, model or service where known, data sources, automated actions, human review points, and current lifecycle status.
Focus on change and evidence
Review model or provider changes, new data sources, expanded users, monitoring results, incidents, exceptions, test evidence, risk acceptances, and overdue actions. Spend more time on material changes and unresolved issues than on unchanged low-risk entries.
Use clear decisions
For each item requiring action, record whether the use case continues unchanged, needs remediation, needs additional review, should be restricted, or should be paused. Name the owner and target review point.
Keep the meeting connected to controls
Use control-owner records, monitoring thresholds, testing evidence, vendor reviews, and incident intake as inputs. Update those artifacts when the review changes the expected operating state.
Keep specialist decisions with specialists
The operating review can coordinate governance but should not substitute for qualified legal, regulatory, clinical, financial, employment, safety, privacy, accessibility, or other professional determinations.
Related knowledge
Use this with AI Use-Case Inventories, AI Governance Control Owners, AI Monitoring Thresholds, AI Testing Evidence, and AI Vendor Review Records.
References
This resource supports operational governance. It does not establish legal compliance or replace qualified legal, regulatory, clinical, financial, employment, safety, privacy, accessibility, or other professional review.