AI Agent Audit Logs: The 12 Fields Auditors Expect

AI agent audit logs provide evidence that tool-using or data-changing agents acted with appropriate authorization, going beyond identity-provider and application logs by recording the decision context, delegation, policy, and resulting side effect. A practical record should capture twelve core elements: the agent identity, human authority or delegation chain, tool and relevant parameters, resource, action, policy ID and version, allow-or-deny decision with an explanation, any human approval, timestamp, request or trace ID, tenant and environment, and the final outcome. The approach aligns with NIST audit-record principles while adding agent-specific details needed to explain why an action was permitted or blocked. Organizations are advised to log denied attempts as well as successful ones, avoid unnecessarily storing sensitive prompts, retain and protect logs according to risk and compliance needs, and correlate authorization records with identity, application, tool, and downstream-system events. Such evidence can support SOC 2 and ISO 27001 logging discussions, though the proposed schema is an engineering pattern rather than a formal compliance requirement.

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