Requested action
What action was actually proposed, by whom or what, and under which context?
AI Agent Audit Evidence
What should an AI agent audit trail actually prove?
An audit trail becomes valuable when it can support a specific execution claim. “The agent logged the request” is different from “the agent had authority, the evidence remained applicable, the committed action matched what executed, and the outcome is reconstructable.” The stronger record connects those stages instead of treating logging as the conclusion.
A useful audit trail should answer more than “what was logged?”
Evidence and authority
What facts and authority supported the action at the relevant time?
Commitment and execution
What action became executable, what actually ran, and did the two correspond?
Changed conditions
Did evidence, authority, limits, identity, or risk state materially change before consequence?
Outcome
What consequence actually followed, including refusal, hold, denial, escalation, or completed execution?
Replay
Can an independent reviewer reconstruct the sequence without relying on unsupported narrative?
Inspectable proof examples
Audit claims need executable examples.
Authority expires before execution
Shows why present authority can require revalidation at the consequence boundary.
Inspect →
Committed action differs from executed action
Shows why commitment-to-execution correspondence matters.
Inspect →
Protected consequence non-formation
Shows the boundary between an internal denial and proof of downstream non-occurrence.
Inspect →
Execution Artifact Registry
Inspect source paths, traces, receipts, hashes, manifests, and claim boundaries across the corpus.
Inspect →
Audit trail versus execution evidence
Logs are often part of the evidence record. The distinction is that execution evidence is proposition-specific: it asks what must be shown to support the exact claim under review. A timestamp, request ID, or denial message may be relevant without proving the complete proposition.
Compare logs with execution evidence →Frequently asked questions
What should an AI agent audit trail contain?
At minimum, enough evidence to reconstruct the requested action, relevant evidence, authority state, material changes, commitment or equivalent execution decision, actual execution, and resulting outcome.
Are normal application logs enough for an AI agent audit?
Sometimes they are useful evidence, but a log entry alone may not establish that authority was valid, that a commitment corresponded to what executed, or that a denied action did not occur through another relevant path.
Does TA-14 require a system to adopt TA-14 terminology?
No. A bounded examination can preserve native terminology and architecture while asking whether the evidence supports the stated execution claim.
Commercial examination + public benefit
Turn one sampled agent action into an evidence question.
The $249 Execution Evidence Snapshot examines one bounded question. Larger authority, failure, changed-condition, or replay problems can move into an Execution Claim Review from $750. Payment buys the examination—not a favorable result. Qualifying paid TA-14 activity also participates in the Environmental Integrity Reinvestment program under the governing terms.