Runtime Compliance

Runtime compliance refers to the monitoring and enforcement of governance policies while AI systems are actively operating in production environments. This ensures that models, data pipelines, and automated decisions continue to meet regulatory requirements, data protection standards, and organizational policies throughout their entire operational lifecycle. For enterprises, runtime compliance is critical because it enables detection of policy violations, data drift, and emerging risks in real time before they escalate into compliance breaches or reputational damage.

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StandardsGlobal2026-08-25

Linux Foundation's TRACE Standard Creates a New Audit Baseline for AI Agents

The Linux Foundation has assumed governance of TRACE (Trust, Runtime Attestation and Compliance Evidence), an open specification developed by AMD, Intel, Microsoft, OPAQUE, and TII. TRACE produces cryptographically verifiable records of how AI agents and confidential workloads execute, drawing on existing standards including RATS, EAT, SLSA, SCITT, SPIFFE, and EAR. Enterprise compliance teams should treat it as an emerging baseline for AI agent auditability across cloud, enterprise, and sovereign infrastructure.

Linux Foundation TRACE AI attestation agentic AI runtime compliance audit trail supply chain security confidential computing