The Audit Trail Problem in Agentic Commerce

When an AI agent approves a payment, who is accountable? Traditional audit infrastructure was not designed for autonomous decision chains — it was designed to reconstruct a human's actions, not an agent's reasoning.

Traditional audit infrastructure assumes a human actor

A conventional audit log answers: which user, logged in from where, clicked which button, at what time. That model assumes a single accountable person at the end of the chain. Agentic commerce breaks that assumption — the "actor" may be a model, invoked by another model, acting under a delegated policy several steps removed from any human decision.

What breaks in an autonomous decision chain

• No single human decision point to point to when a transaction is challenged
• Intermediate reasoning steps aren't captured in a form an auditor can evaluate
• Delegation of authority across multiple agents dilutes accountability further with each hop
• Existing logs record what happened, not whether it was authorized to happen

An audit trail that only proves a transaction occurred isn't an audit trail — it's a receipt. Accountability requires proving the transaction was authorized before it happened.

Rebuilding accountability for agentic systems

Closing this gap means capturing the authorization decision itself — not just its outcome — as part of the transaction record. That's the foundation agentic commerce infrastructure has to be built on, not bolted onto afterward.