An agent audit trail links actions to the responsible agent identity, owner, task, instruction source, tool, timestamp, input, output, approval, and resulting external state. It supports review, debugging, compliance, incident response, and accountability.
Logs must be protected from agent tampering and avoid exposing unnecessary secrets or personal data. Important records should be complete, time-ordered, retained under policy, searchable, and tied to evidence from the target system rather than only the agent's description.
ELI5
An agent audit trail is a lasting record of what an AI agent was asked to do and what it actually did. It can show the tools it used, approvals it received, results it observed, and changes it made.
For example, if an agent updates a customer account, the audit trail can record which account was targeted, which rule allowed the change, and whether the update succeeded. A reviewer can then investigate a mistake without relying on memory or guesswork.
What should an agent audit trail record?
It can record identity, owner, task, instructions, provenance, tool calls, inputs, outputs, approvals, timestamps, errors, and verified state changes.
How should agent audit logs be protected?
Use access controls, integrity protection, minimal sensitive data, retention policy, immutable storage where appropriate, and monitoring for missing records.
