The Requirement-Fit Gate: Using AI to Judge Whether Work Meets Approval Criteria

The second compliance gate is the hardest: does the work actually meet the requirement? Completeness is mechanical. Requirement fit is judgment. This is where AI earns its keep — and where responsible design matters most.

What "meets the requirement" really means

Approval criteria are rarely a checklist. They're a standard: "documentation must support the coding decision," "disclosure must be clear to a lay reader," "risk assessment must address all material factors." A human reviewer weighs the artifact against the standard. AI can do the same weighing — quickly, consistently, at every submission.

How the gate works

At submission, the AI receives the artifact, the criterion, and any reference exemplars. It returns a fit assessment with cited evidence from the artifact — the specific sentence or field that supports (or contradicts) the criterion. The reviewer sees the reasoning, not just a verdict.

Why cited evidence is non-negotiable

A yes/no verdict is a black box. A verdict plus quoted evidence is auditable. Reviewers can accept, challenge, or override in seconds because the AI showed its work.

Where humans stay in charge

• Edge cases route to human review by default.
• Any confidence below threshold routes to human review.
• Overrides are logged with reasons and reviewed monthly for rule drift.

The trap to avoid

Don't ask the AI to approve. Ask it to assess. Approval is a role; assessment is a check. Keeping that boundary clean is what makes the gate defensible under audit.

Silverberry helps design these judgment-layer checks through AI Consulting Services.