AI Audit Trail
Definition
A chronological record of all actions taken by or on behalf of an AI system, including: proposed actions, evaluation decisions (allow/block), policy rules applied, state at time of evaluation, and execution outcomes. AI audit trails must be immutable (tamper-resistant), complete (every action recorded), attributable (every action traceable to an agent and user), and exportable (usable for compliance reporting).
Why It Matters
Regulators, auditors, and enterprise security teams need evidence of AI governance. "We told the model to be safe" is not evidence. An immutable, cryptographically chained audit trail that records every evaluation decision is evidence. Without audit trails, AI governance is unverifiable.
How Exogram Addresses This
Every Exogram evaluation generates an immutable audit record: proposed action, evaluation result, state hash, applied policy rules, and signed token. Records are cryptographically chained and exportable for compliance reporting. The audit trail is built into the infrastructure, not bolted on.
Related Terms
Key Takeaways
- → This concept is part of the broader AI governance landscape
- → Production AI requires multiple layers of protection
- → Deterministic enforcement provides zero-error-rate guarantees