Blog · · Jiber Team
What a good audit log for an AI agent should contain.
An AI agent audit log is a tamper-evident record of each input, decision, human approval and downstream action an agent takes.
TL;DR: A good AI agent audit log records every input, every decision with the rule or model output behind it, every human approval or edit, and every action taken in other systems, with timestamps. It should be tamper-evident, retained according to your policy and searchable by case.
Why do AI agents need audit logs?
Audit logs turn an agent from a black box into a system you can inspect. They matter for three reasons: compliance, debugging and trust. When someone asks "what happened here?", the log should answer it.
Jiber is an AI company that builds process agents for businesses. Every agent combines fixed business rules with AI reasoning, pauses for human sign-off at chosen checkpoints, and writes each step to an audit log.
What should each audit log entry contain?
A useful entry captures the full story of a step. At minimum, record:
- The input. What the agent received, when, and from which source system.
- The decision. What the agent concluded and why: the rule that fired, or the model output and the prompt or model version that produced it.
- Human involvement. Who approved, edited or rejected a step, what they changed, and when.
- The action. What was done in downstream systems, with identifiers so the change can be traced or reversed.
- The timestamp. A consistent time for every entry, so steps can be put in order.
How should rules and AI decisions be logged differently?
Rule decisions are deterministic, so log the rule and its version alongside the values it checked. Anyone can then reproduce the result.
AI outputs are not always reproducible, so log the output itself, any confidence signal, and the version of the prompt or model used. If a field was flagged as uncertain and sent to a person, the log should show that too.
What does this look like in a real workflow?
In Form 1120 tax preparation, the log might show each client document received, the figures extracted, an exception raised for a missing value, and the preparer who signed off the draft. In recruiting, it shows how a profile was scored and who approved the shortlist. In real estate, it shows each enquiry, the reply drafted and who approved sending it.
How should audit logs be stored and searched?
Logs are only useful if they can be trusted and found. Good practice includes:
- Making logs tamper-evident, so entries cannot be changed silently
- Retaining them according to your own policy and any rules that apply to you
- Limiting access to the people who need it
- Making them searchable by case, client or record
With these in place, answering a question about a past case takes minutes rather than days. Our security page and platform page explain how this fits into the wider design.
Frequently asked questions
What is an AI agent audit log?
It is a time-ordered record of everything an AI agent did on a case: the inputs it received, the decisions it made and why, any human approvals or edits, and the actions it took in other systems.
Should prompts and model versions be logged?
Yes. Because AI outputs are not always reproducible, recording the output together with the prompt or model version helps explain a result later.
How long should audit logs be kept?
That depends on your own retention policy and any regulations that apply to your business.
Who should have access to audit logs?
Access should be limited to the people who need it, such as process owners, reviewers and auditors.
Want to see what an audit log looks like for your own process? Book a demo and we will show you a sample.