Product · Readiness Diagnostic

High-Risk AI Decision Readiness Score.

Twelve questions. They measure whether your organization can prove, not assert, that a human is still meaningfully overseeing the AI decisions you ship. Answer honestly; the score is for you.

01Before a high-risk AI decision reaches a human reviewer, is it automatically triaged by risk level so the highest-risk decisions get the most scrutiny?
02Can you replay any past AI-assisted decision -- exactly as it unfolded, including the AI recommendation, the evidence the reviewer saw, and the final human decision -- without reconstructing it after the fact?
03When a human reviewer disagrees with the AI recommendation and overrides it, is the reason for that override captured in a structured, auditable format?
04Do you know, right now, what percentage of AI recommendations your human reviewers are accepting without modification -- and whether that rate has changed over the past six months?
05Do you have a way to measure whether your human reviewers are catching errors in AI output -- not just approving or rejecting, but actively detecting mistakes the AI made?
06Is there any way to distinguish a reviewer who thoroughly examined the evidence from one who rubber-stamped the AI recommendation in five seconds?
07After your AI system makes a visible mistake that a reviewer catches, do you measure whether that reviewer's behavior changes appropriately afterward?
08Could your reviewers make accurate decisions on high-risk cases if the AI system were unavailable -- and do you have data to support that claim?
09For AI decisions involving protected-class factors, adverse actions, or outcomes that could be legally challenged (denials, terminations, eligibility decisions), are domain-specific rules enforced automatically at the decision layer -- not just documented in policy?
10If a regulator asked you today for evidence that your AI-assisted decisions involve genuine human oversight -- not just a human in the loop -- how ready is that evidence?
11Do you monitor judgment quality trends across your reviewer population -- not just individual incidents -- to detect systemic drift before it becomes a compliance or liability event?
12Which best describes your organization's AI oversight goal for the next 12 months?
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