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Glossary

Audit Trail

An audit trail is the tamper-evident record of everything that happened to a piece of work: what arrived, what the AI extracted and proposed, which evidence grounded each answer, who approved what, and which actions executed. It lets teams reconstruct and prove any outcome end to end — essential for compliance, debugging, and trust in automation.

Synonyms: audit log, activity log, execution history, decision log

An audit trail is what turns automation from a black box into a system of record. In a governed AI workflow, every state transition appends to the trail: the request as it arrived, the structure extracted from it, the sources cited in each answer, the proposals raised, the approvals that gated them, and the actions that finally executed. Because entries are attributed and time-stamped, the trail supports three distinct jobs — compliance reviews that need proof of authorization, debugging sessions that need to see exactly what the model was shown, and operational metrics that need reliable ground truth about how work actually flowed.

Frequently asked questions

What does an audit trail capture in AI work automation?
Each event in a work item's life: intake and its source channel, extracted fields, retrieved evidence and citations, the AI's proposals, every approval or rejection with actor and timestamp, and the executed actions with their results.
Why does an audit trail matter for AI specifically?
AI decisions are probabilistic, so accountability has to come from the record rather than the rule. A complete trail shows what the model saw, what it proposed, and who authorized the outcome — turning otherwise opaque automation into something reviewable and defensible.