Governance-Aware Agent Telemetry for Closed-Loop Enforcement in Multi-Agent AI Systems

arXiv cs.LG / 4/8/2026

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Key Points

  • The article highlights an “observe-but-do-not-act” gap in enterprise multi-agent AI systems: telemetry tools record inter-agent dependencies but do not enforce governance policies in real time.
  • It proposes Governance-Aware Agent Telemetry (GAAT), a reference architecture that links telemetry collection directly to automated policy enforcement for multi-agent workflows.
  • GAAT extends OpenTelemetry via a Governance Telemetry Schema (GTS) to capture governance attributes needed for enforcement-relevant analysis.
  • The design includes a real-time policy violation detection engine using OPA-compatible declarative rules with sub-200 ms latency, plus a Governance Enforcement Bus (GEB) supporting graduated interventions.
  • To ensure integrity of governance inputs, GAAT adds a Trusted Telemetry Plane with cryptographic provenance for trustworthy telemetry-to-enforcement coupling.

Abstract

Enterprise multi-agent AI systems produce thousands of inter-agent interactions per hour, yet existing observability tools capture these dependencies without enforcing anything. OpenTelemetry and Langfuse collect telemetry but treat governance as a downstream analytics concern, not a real-time enforcement target. The result is an "observe-but-do-not-act" gap where policy violations are detected only after damage is done. We present Governance-Aware Agent Telemetry (GAAT), a reference architecture that closes the loop between telemetry collection and automated policy enforcement for multi-agent systems. GAAT introduces (1) a Governance Telemetry Schema (GTS) extending OpenTelemetry with governance attributes; (2) a real-time policy violation detection engine using OPA-compatible declarative rules under sub-200 ms latency; (3) a Governance Enforcement Bus (GEB) with graduated interventions; and (4) a Trusted Telemetry Plane with cryptographic provenance.