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AI Use-Case Records: The Minimum Evidence to Keep Before Deployment

A practical governance record for documenting AI purpose, ownership, data, testing, oversight, risk decisions, and review triggers.

Shamar Bennett August 20, 2026 Updated August 18, 2026 Reviewed 2026-08-18 Version 1.0 1 min read

An AI inventory tells you what exists. A use-case record explains why a system exists, what it is allowed to do, and the evidence behind the decision to use it.

Record the purpose and owner

Document the business problem, intended users, accountable owner, affected process, and the decisions or actions the system may influence.

Describe data and dependencies

Record important data categories, connected systems, external providers, permissions, retention assumptions, and restrictions on sensitive information.

Capture testing and limitations

Keep the acceptance criteria, representative tests, known failure modes, unresolved limitations, and the conditions under which the system should not be used.

Define human oversight

State which actions require approval, who reviews exceptions, what authority reviewers have, and how users can report unexpected behavior.

Set review triggers

Revisit the record when the use case, model, data, permissions, vendor, affected population, or legal and operating context changes.

Related knowledge

Use this record alongside AI risk classification, human-review models, internal AI policy, and vendor due diligence.

References

This is operational governance guidance, not a determination of legal compliance or suitability for regulated professional decisions.

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About the author

Shamar Bennett

Tavryqen authors contribute practical perspectives on responsible AI, automation, security, and technology transformation.