Governance is difficult to verify when important decisions exist only in meetings or chat messages. Useful evidence connects an AI-enabled use case to its owner, approved boundary, reviews, tests, incidents, and material changes.
Preserve the decision trail
Keep the business purpose, accountable owner, approved users and systems, data conditions, human-oversight points, known limitations, and the basis for material approvals or exceptions.
Keep testing evidence proportionate
Record what was tested, the environment or version, relevant acceptance criteria, material findings, remediation, and who accepted residual risk. Evidence should be understandable later without implying that testing proves universal safety or compliance.
Connect incidents and changes
Link significant incidents, complaints, control failures, model or vendor changes, new data sources, and expanded permissions back to the use-case record so reviewers can see whether reassessment is needed.
Respect professional boundaries
Operational records can support oversight, but they do not establish legal compliance, clinical suitability, financial appropriateness, employment fairness, safety, or other regulated conclusions unless qualified reviewers make those determinations under the applicable framework.
Related knowledge
Use this guide with AI Use-Case Approval Records, AI Incident Escalation, AI Risk Classification, and AI Change Management.
References
This resource supports operational governance and does not replace qualified legal, regulatory, clinical, financial, employment, safety, or other professional review.