Topic starter
24/10/2026 8:47 pm
TL;DR: AI agent traces remain intent records, with Kovrr showing they can inventory agents, reconstruct sessions, and flag unusual activity. For governance, that means OpenTelemetry needs identity and control-plane evidence before it can support assurance or investigation.
Editorial analysis by NHI Mgmt Group, based on content published by Kovrr: “What OpenTelemetry Can and Cannot Tell You About Your AI Agents”.
Key questions
Q: Why do AI agent logs need to be joined with identity and cloud records?
A: Because the agent's own record is usually an intent record, while identity and cloud systems carry the enforcement or outcome record.
Q: What are the signs that AI agent telemetry is too weak for investigation?
A: If security teams can see prompts but cannot reconstruct tool invocations, retrievals, or data egress on the same principal, telemetry is incomplete.
Q: What breaks when AI agent telemetry is used as proof of authorisation?
A: It breaks at the accountability step.
Practitioner guidance
- Instrument independent corroboration paths Correlate agent telemetry with cloud audit, identity, and application logs so an agent's claimed action can be verified outside its own record.
- Treat telemetry configuration as a control surface Monitor writes to agent telemetry settings and alert when export stops, because a silent stream can indicate disabled observation rather than low activity.
- Validate vendor field conformance before rule writing Check which span attributes are stable, which are custom, and which versions your detections depend on before you encode governance rules.
Bottom line: OpenTelemetry can improve AI agent visibility, but it does not by itself prove authorisation, completion, or accountability.
Glossary terms: Intent-to-Effect Gap, Agent telemetry, Action Record, Semantic Convention Stability
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This topic was modified 6 days ago by NHI Mgmt Group
25/10/2026 11:11 am
AI agent telemetry is an observation layer, not an assurance layer. OpenTelemetry can reveal what an agent attempted, but assurance requires proof that the record is complete, independent, and resistant to manipulation. That distinction is central to AI governance because telemetry emitted by the subject being watched cannot, by itself, satisfy the controls that ask who authorised what. Practitioners should treat telemetry as evidence input, not evidence finality.
A few things that frame the scale:
- 54% of organisations are actively deploying AI agents across workflows, yet only 21% report a mature governance model for agentic AI.
A question worth separating out:
Q: Should teams treat OpenTelemetry or control-plane audit logs as the primary source of truth?
A: Control-plane audit logs should usually carry more weight for assurance because they are written by the platform and often record the enforcement outcome. OpenTelemetry still matters for session context and tool-use visibility, but it is better treated as a supporting record. The practical model is corroboration, not competition, between the two sources.
👉 Read our full editorial: OpenTelemetry shows agent intent, not assurance, for AI governance
This post was modified 6 days ago by NHI Mgmt Group