AI Governance Institute logo
AI Governance Institute

Practical Governance for Enterprise AI

Agentic AI
AGT · Agentic AIAGT-014Medium effortAgent-relevant

Multi-Agent Delegation Chain Logging

Log and attribute every action in a multi-agent system with sufficient detail to trace any action back to its originating instruction, authorized agent, and human principal.

Objective

Maintain an auditable chain of custody across multi-agent architectures so that any action — including those taken by deeply nested subagents — can be traced to the human principal who initiated it.

Maturity Levels

1

Initial

Agent actions are logged individually but without parent-task context; delegation chains cannot be reconstructed.

2

Developing

Orchestrator-level actions are logged with task IDs, but subagent actions reference only the calling agent, not the originating instruction.

3

Defined

Every agent action is stamped with a trace ID that links it to the originating human request, delegating agent, and authorization scope.

4

Managed

Delegation chain logs are queryable; compliance teams can reconstruct any action chain on demand within the audit trail SLA.

5

Optimizing

Trace IDs propagate automatically through all agent frameworks in use; gaps in chain coverage trigger automated alerts.

Evidence Requirements

What an auditor or assessor would expect to see for this control.

  • Logging schema documentation showing trace ID propagation fields and delegation chain structure
  • Sample reconstructed delegation chains demonstrating end-to-end traceability from human instruction to subagent action
  • Tamper-evidence controls documentation (append-only store, log integrity verification)
  • Maximum delegation depth policy and alerting configuration
  • Audit trail retrieval demonstration: ability to pull a complete delegation chain within the defined SLA

Implementation Notes

Key steps

  • Assign a globally unique trace ID to every human-initiated task; propagate this ID to every spawned subagent and every tool call.
  • Log at minimum: trace ID, parent task ID, agent ID, action type, inputs, outputs, authorization scope active at time of action, and timestamp.
  • Ensure logs are append-only and tamper-evident — agent systems should not be able to modify their own logs.
  • Define the maximum delegation depth permitted per task; alert when chains exceed this limit.
  • Require that any agent that spawns another agent records both the delegation instruction and the scope it is passing to the subagent.

Example Implementation

Legal team deploying a contract review orchestrator with document retrieval and clause analysis subagents

Delegation Chain Log — Trace ID: cr-20260531-0047

SeqAgentActionInputs (summary)Auth scopeParent task
1Human (jsmith)Initiate contract reviewContract ID 9921Full access
2OrchestratorSpawn retrieval agenttrace_id=cr-20260531-0047, doc=9921read:contractshuman-1
3Retrieval AgentFetch documentdoc=9921read:contractsorchestrator-2
4OrchestratorSpawn clause agentsections=[3,7,12]read:contractshuman-1
5Clause AgentAnalyze section 7section_text=...read:contractsorchestrator-4
6OrchestratorCompile reportclause_results=...write:reportshuman-1

Control Details

Control ID
AGT-014
Typical owner
AI Engineering / Audit & Compliance
Implementation effort
Medium effort
Agent-relevant
Yes

Tags

multi-agentaudit traildelegationtraceabilityagentic AI