AI Agent Evidence Retention Policy for Auditors
An AI agent evidence retention policy defines what agent activity records must be captured (tool calls, permission grants, policy decisions, identity attestations), how long each category is retained, and how integrity and access are controlled so auditors can reconstruct and verify agent behavior. No single AI-specific regulation currently sets these parameters, so policies must be built from adjacent frameworks such as NIST SP 800-53, the EU AI Act, and ISO/IEC 42001.
Chain-of-Custody and Access Control Requirements
- Restrict modification and deletion rights on audit records to a limited administrative role, consistent with least-privilege principles.
- Log access to the audit records themselves, separate from the underlying agent activity logs, so viewing or exporting evidence is traceable.
- Distinguish retention rules for raw runtime logs from summarized audit reports, since auditors may require both levels of detail.
- Maintain a documented legal-hold process that extends retention automatically when an audit or incident investigation is active.
- Ensure retained logs remain queryable rather than simply archived, so reconstruction of an agent decision sequence is feasible on request.
Core Evidence Categories for AI Agent Audits
Each category below answers a distinct audit question and should be captured and retained separately rather than collapsed into one log stream.
Tool-Call Records
What the agent invoked, with what parameters, and the result returned.
Permission Grants
Authorization decisions that allowed or denied agent access to tools or data.
Policy Enforcement Decisions
Runtime governance actions that allowed, blocked, or modified agent behavior.