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Why agentic GRC fails audits, and what to demand instead
The auditor does not ask what the AI did. The auditor asks who approved it, on what evidence, and where that is recorded.
Autonomous compliance AI is marketed on outcomes: the platform detects, decides and acts. In a certification-prep context that is convenient. In front of a regulator it is the exam question, because the audit trail of an autonomous system is a log of what the machine chose, not a record of human accountability.
The defensible pattern is proposal, not action. AI drafts the mapping, the answer, the classification, each output carrying its source and a confidence score. A human accepts or rejects, and that decision is the recorded act. The auditor gets a chain they can walk: proposal, citation, approver, timestamp.
What to demand from any GRC AI: tenant-scoped retrieval only, per-output citations, confidence shown, recorded human approval as a first-class action, and an exportable trail. If a vendor cannot show the accept/reject log, the autonomy is a liability wearing a feature's clothes.
Reviewed September 2026.
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