Compliance & Regulatory
AI Audit Trail
A chronological record of all AI-related decisions, reviews, approvals, and policy changes within an organization.
An AI audit trail is the documentation that records every significant action in an organization's AI governance program: who requested which tool, what risk assessment was performed, who approved or denied it, what policies were applied, and how the decision was communicated. A complete audit trail captures:
- Tool requests and their evaluation history
- Risk scores and the criteria used to calculate them
- Approval/denial decisions and the rationale
- Policy changes and who authorized them
- Shadow AI discoveries and the remediation actions taken
- Periodic review outcomes for previously approved tools
The audit trail serves as evidence that governance decisions were made systematically and can be reviewed — not just that a policy exists on paper.
Why it matters
When a regulator asks how you decided to allow a specific AI tool, 'we reviewed it' isn't sufficient. They want to see the assessment, the decision, the approver, and the date. An audit trail provides that evidence automatically.