AAISM Domain 1 AI Governance Practice Test 2026 – Full Study Guide

At the heart of this question is the order of activities used to assess an AI system: Testing, Evaluation, Verification, and Validation. The progression starts by testing to measure how the system performs against its specifications. Next, evaluation looks at broader concerns—how well the system meets objectives, risks, and context, ensuring alignment with stakeholder needs. Then verification checks that the system has been built correctly and consistently with its design. Finally, validation confirms that the system actually solves the intended problem for real users in real conditions, i.e., that it is fit for its purpose.

This sequence makes sense because you first probe capabilities, then assess fit and risk, then confirm correct construction, and only after that confirm real-world usefulness. Verification versus Validation differ in focus: verification is about “built right” (conformance to design), while validation is about “built for the right problem” (meeting user needs in practice).

The other orders disrupt this flow by placing validation before verification or by rearranging the testing and evaluation steps, which weakens the logical progression from technical correctness to real-world usefulness.