AI audit logs need to serve two purposes at once. They should help teams understand what happened, and they should support compliance evidence. Logging everything is not the answer. Over-collection can create privacy, security, and retention problems. The better approach is to capture the events needed to reconstruct meaningful decisions and control operation.
The right fields depend on the system, but several categories are consistently useful.
System and user context
Log the AI system or agent ID, version, environment, owner, user or service account, user role, session ID, timestamp, and request source. This lets teams connect events to the correct inventory record and permission context.
Without system context, logs become hard to use during audit or incident review.
Input and output summaries
For sensitive systems, consider storing summaries, hashes, redacted content, or references instead of full prompts and outputs. The logging design should balance forensic value with privacy and confidentiality.
Capture enough to understand the purpose of the interaction, the type of data involved, and whether policy checks were triggered.
Tool calls
For agents, tool calls are central evidence. Log tool name, action type, target resource, permission used, parameters summary, outcome, and error state. For write actions, record whether the action was approved, rejected, edited, or rolled back.
Tool-call logs often reveal the difference between a harmless assistant and an operational agent.
Policy and guardrail decisions
Capture allow, block, redact, escalate, require approval, override, and fail-closed events. Include the policy rule or control name where possible. This helps prove that runtime controls operated, not merely that they were documented.
Human review and incidents
Log reviewer identity, decision, rationale, timestamp, and related agent output when human oversight is required. Link incidents to affected systems, events, root cause, remediation, and closure.
AI audit logs should be designed with retention, access control, redaction, and evidence retrieval in mind. The best logs are not the largest logs. They are the logs that answer what happened, why it was allowed, and which control applied.