AI Audit Trail
An AI audit trail is the persistent, tamper-evident record of every input, output, tool call, model version, and decision an AI system has made, sufficient to reconstruct any past interaction.
What is AI Audit Trail?
An audit trail captures the prompt, retrieved sources, model and version, parameters, output, tool calls, and the human decisions wrapped around them. It must be retained for the period required by sectoral regulation (often 5-10 years) and must support targeted retrieval for a specific user, time, or interaction. Audit trail design is one of the highest-leverage architectural decisions in regulated AI.
How does AI Audit Trail apply to enterprise AI?
Auditable AI is the table stakes for enterprise procurement in finance, legal, healthcare, and the public sector. Without an audit trail, the system cannot answer regulator questions or GDPR right-of-access requests.
Related terms
- Observability - Observability for AI is the ability to understand what an AI system did, why it did it, and at what cost, by inspecting its inputs, outputs, intermediate steps, and metrics.
- AI Risk Management - AI risk management is the discipline of identifying, assessing, mitigating, and monitoring the harms an AI system can cause across its lifecycle.
- Transparency Notice - A transparency notice is a clear disclosure to users that they are interacting with an AI system, what it is doing with their data, and what its limits are.
- EU AI Act - The EU AI Act (Regulation (EU) 2024/1689) is the European Union's horizontal regulation for AI, classifying systems by risk and imposing obligations on providers, deployers, importers, and distributors.
External references
Need help applying AI Audit Trail to your enterprise? Submit a short brief and we reply within one business day.