Agent audit trail
gobernanzaAI audit trail · agent action provenance · auditable agent log
A complete, tamper-evident record of what an AI agent did and why: what it was asked, what data it used, which tools it called, what it decided, who approved it and how it ended.
An agent audit trail is the proof of its actions. Unlike a technical log, which exists so the team can debug, an audit trail exists so an outsider can reconstruct an episode months later without taking anything on faith. A usable trail typically records, at minimum: agent identity and running version, the instruction or trigger that activated it, the context and data sources consulted, every tool call with input parameters and response, the decision or action executed, the approval state (automatic or human), the outcome, and any exceptions, interrupts or rollbacks. Two properties separate it from an ordinary log: integrity — tampering must be evident — and retention — it has to outlive the incident. This artefact became urgent because an agent acts with no human present: when something goes wrong, the organisation cannot reconstruct intent by asking whoever did it, because whoever did it is a process. The trail is a detective control and pairs with guardrails, which are preventive: guardrails block the wrong action in the moment; the trail documents what actually happened. Having one without the other leaves half the problem open.
How it differs from
- Application log
- Logs exist to debug and are usually rotated and overwritten; an audit trail must be tamper-evident, retained and legible to someone who was not there.
- Agent observability
- Observability watches aggregate performance (latency, cost, success rate); the trail reconstructs one specific episode end to end.
- Guardrails
- Guardrails are preventive and block an action before it happens; the trail is detective and documents what did happen.
FAQ
- What are the minimum fields?
- Agent identity and version, trigger, context and sources used, each tool call with input and output, the executed action, approval state, outcome, and any exception or rollback. Without approval state and agent identity the trail fails to answer the question a third party actually asks: who authorised this.
- How long should it be kept?
- Longer than the incident lasts and shorter than data protection allows — two limits pulling in opposite directions. The right answer is a written retention policy per system type, not the tool's default. Keeping everything forever is not prudence, it is a different risk.
- Is my agent platform's built-in trace enough?
- Rarely as-is. Platforms log to debug: short retention, no integrity guarantee, and human approval state often missing. Exporting the fields that matter into your own store with defined retention and access control is usually required.