Audit Trail
An audit trail is a tamper-evident log of every action an AI employee took — prompts, model responses, tool calls, approvals, outcomes — used for compliance, debugging, and accountability.
When an AI sends an email, modifies a record, or makes a decision, you need to be able to answer later: who decided, with what input, using which model, why. The audit trail is that record. It's the difference between 'we use AI' and 'we can prove how the AI used your data'. Audit trails are required (in spirit, often in law) by SOC 2, HIPAA, GDPR right-to-explanation, NYC Local Law 144, and the EU AI Act for high-risk systems. They're also the single most useful debugging artifact in agentic systems.
Example
A customer disputes a refund denial. The audit trail shows: ticket received, AI classified as 'outside policy', model used (Claude 4.7), prompt with policy doc, full response, decision logged. The dispute is resolved in five minutes with evidence.
How OpenLabor uses it
Every OpenLabor run generates a tamper-evident audit trail with full prompts, tool calls, model versions, and approver identity.
How long should I retain audit trails?
Match the retention policy of your other operational logs — typically 1–7 years depending on industry.
Are audit trails required by law?
For some uses yes (NYC bias audits, EU AI Act high-risk). For most uses they're best practice rather than mandate. Either way, they're cheap insurance.
Related: run, approval-gate, guardrails.
AI Labor Glossary