An AI audit trail logs system interactions: the queries or documents submitted, the sources retrieved, the outputs generated, the model version used, and the human review and edits applied afterward.
It differs from data lineage, which traces how information was transformed, by focusing on actions, actors, and timing.
Alternative Names:
AI Audit Log, AI Activity Log
Why it Matters?
Audit trails are how an organization demonstrates supervision after the fact. If a client, court, or regulator asks what AI touched a matter and who reviewed the output, the log is the answer. It also supports incident investigation: when an error surfaces, the trail identifies which other work used the same model version and may need re-checking.
Frequently Confused with
Related terms
Frequently asked questions
What should an AI audit trail capture?
Why does model version matter in the log?
