Assess whether the system is high-risk under the EU AI Act (12e02a)
August 31, 2026
SITUATION An internal audit finding that human review logs are empty put post-deployment drift report the owner never signed in front of vendor-diligence reviewer for AI tools in a bank preparing for a model-risk exam. This AI Governance / Bias and Training Data decision is the system is high-risk from post-deployment drift report the owner never signed, and the live options are Policy or governance breach, Model defect, Dual failure.
DECISION Vendor-diligence reviewer for AI tools in a bank preparing for a model-risk exam must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using post-deployment drift report the owner never signed after an internal audit finding that human review logs are empty.
HYPOTHESES TO TEST 1. Authorize Policy or governance breach now; post-deployment drift report the owner never signed already has the discriminator after an internal audit finding that human review logs are empty. 2. Keep Model defect in force until post-deployment drift report the owner never signed is completed after an internal audit finding that human review logs are empty for vendor-diligence reviewer for AI tools. 3. Treat post-deployment drift report the owner never signed as Dual failure because both readings appear after an internal audit finding that human review logs are empty. 4. Refuse a AI Governance close: vendor-diligence reviewer for AI tools does not have the decision the system is high-risk turns on in post-deployment drift report the owner never signed.
ANALYSIS REQUIRED 1. Map the approved-use case to the system the system is high-risk would bind. 2. Check intended purpose and inventory status against EU AI Act / exam-readiness language after an internal audit finding that human review logs are empty. 3. Map the approved-use case to the system the system is high-risk would bind. 4. For this AI Governance Bias and Training Data file, read post-deployment drift report the owner never signed against an internal audit finding that human review logs are empty and write the one fact that would move the system is high-risk for vendor-diligence reviewer for AI tools.
RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance / Bias and Training Data packet (post-deployment drift report the owner never signed after an internal audit finding that human review logs are empty). The follow-on Bias and Training Data action is what vendor-diligence reviewer for AI tools does next: implement the option, assign an owner, and log the missing fact.
COMMAND RETURNS - Bottom-line AI Governance option on the system is high-risk, then the evidence in post-deployment drift report the owner never signed, then the action for vendor-diligence reviewer for AI tools - Hypothesis scorecard against post-deployment drift report the owner never signed: supported / rejected / untestable - Missing page in post-deployment drift report the owner never signed after an internal audit finding that human review logs are empty, if any - Regulatory or exam hook Bias and Training Data would cite
Explore more
More AI Governance prompts
- Assess whether training data has a lawful basis and documented lineage
- Assess whether the inventory can be represented to an examiner as complete
- Assess whether a generative-AI incident is a policy breach or a model defect
- Assess whether explainability artifacts would survive an exam (d7cb7b)
- Assess whether human review is real or a rubber stamp (f156ff)
Explore related decision areas
See governed multi-model AI on your own prompt
Compare GPT-5, Claude, and Gemini side by side, with human review and a decision record built in.

