Evaluation before expansion
Test representative cases, edge conditions, harmful failure modes, latency, and cost against approved acceptance criteria.
A responsible system makes permissions, tests, review gates, failure behavior, monitoring, and operating decisions explicit.
Operating method, not a certification or legal assurance. Requirements still depend on the workflow, jurisdiction, and risk.
A policy statement does not limit access, interrupt an action, route an exception, or restore the previous state. The control has to exist in the operating path.
Test representative cases, edge conditions, harmful failure modes, latency, and cost against approved acceptance criteria.
Bind source access and tool use to identity, least privilege, data boundaries, and a named operating owner.
Give reviewers enough evidence, time, and decision rights to approve, reject, correct, or escalate an action.
Route uncertainty and failure into a queue with priority, context, ownership, and a service expectation the team can honor.
Define the safe deterministic or human-operated path that keeps the workflow moving when the AI path is unavailable or unsuitable.
Preserve the prior state, action record, and recovery steps needed to reverse a consequential change.
Map the requirements to the actual system.
NIST frames AI risk management across the design, development, use, and evaluation of AI systems. The European Commission describes risk-based obligations that include documentation, logging, human oversight, monitoring, robustness, and accuracy for covered uses.
Sources reviewed July 31, 2026. This page is not legal, compliance, or security advice.
Use the evaluation and governance checklist to expose missing owners, tests, and recovery paths.
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