What is approval workflow in AI compliance?
Approval workflow in AI compliance is the enforced sequence that routes an AI system from completed screening and evidence review through a named supervisor who sees the full governance basis before making a decision. The supervisor may approve, reject, request additional completion, or approve with conditions.
Each outcome is a structured governance event with attribution. The workflow cannot be bypassed — there is no path from screening to "approved" without passing through the approval gate.
Key points
- The approval workflow is enforced by the platform, not by policy. A system cannot be marked as approved without a supervisor reviewing the governance basis.
- The supervisor sees everything: screening result, classification, obligation mapping, evidence state, and any open gaps or non-applicability determinations.
- Four outcomes are possible: approve, reject, request completion, or conditional approval. Each is logged with attribution and rationale.
- Overrides are permitted but governed. A supervisor who approves despite open gaps must document the rationale, and the override becomes part of the permanent record.
Why it matters
Without an enforced approval workflow, AI systems exist in a permanent grey zone — screened but not approved, documented but not governed. The approval workflow creates the definitive governance event that separates "under review" from "approved for use." It is the moment where organisational accountability becomes concrete and traceable.
How EAB approaches this
EAB's Supervisor Approval implements a structured approval workflow. The supervisor reviews the complete governance basis before deciding. Risk Acceptance Workflow handles conditional approvals with documented rationale. The audit trail preserves every approval decision with full context.