AI Auditability and the EU AI Act: Why Execution Evidence Matters

As AI systems become more widely used in regulated environments, the need for auditability is becoming critical. The article discusses how the EU AI Act requires AI systems to be traceable, transparent, and accountable, and how most current systems lack the necessary execution integrity to meet these requirements.

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As AI systems move from experimentation into regulated environments like finance, healthcare, and law enforcement, the need for auditability is becoming unavoidable. The EU AI Act establishes clear expectations around traceability, record-keeping, transparency, and accountability for high-risk AI systems. However, most AI systems today are not built to support real auditability. They rely on logs and traces, which are designed for observability but not for reconstructing and validating what actually happened during execution. Execution integrity, which means producing a complete, tamper-evident, and verifiable record of what ran, is the missing piece. Certified Execution Records (CERs) provide a way to capture this execution evidence, binding together inputs, parameters, runtime conditions, and outputs in a cryptographically verifiable artifact. This changes the model from 'Execution -> Logs -> Reconstruction' to 'Execution -> Evidence -> Verification', directly supporting the EU AI Act's requirements around traceability, record-keeping, transparency, and accountability.