Audit Log (AI)
The immutable record of prompts, retrieval events, tool calls, model choices, and outputs.
What is Audit Log (AI)?
An AI audit log is the source of truth when something looks wrong: a sensitive output, a regulator request, or a misbehaving agent. It needs to capture timestamps, user identity, agent identity, retrieved sources, tool calls, and model decisions. See AI Agent Observability: Logs, Traces, Audit.
What is an example of Audit Log (AI)?
When an agent sends an incorrect customer notice, investigators can reconstruct the user request, policy version, retrieved document passages, model and prompt version, tool arguments, approval decision, and final message from one trace ID.
How is Audit Log (AI) different from related concepts?
Operational logs help teams run a system. Audit logs provide durable evidence of who or what performed an action, under which policy, and with what result. One event stream can serve both only if integrity and retention requirements are met.
What should enterprises evaluate for Audit Log (AI)?
- Capture complete decision context without logging secrets, access tokens, or unnecessary personal data.
- Use append-only or tamper-evident storage and tightly control who can view or export traces.
- Verify that a reviewer can replay the chain of events across the model, retriever, orchestrator, and external tools.
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