Question 14
Domain 2 — AI Operations, Lifecycle, and Control EnvironmentThe PRIMARY goal of champion-challenger testing in AI model deployment is to:
Correct answer: C
Explanation
Champion-challenger testing compares a "champion" production model with a "challenger" candidate model to see whether the new model performs better before replacing the current system. Its primary purpose is to validate performance and reduce deployment risk by testing the challenger against the model already in production.
Why each option is right or wrong
A. Test a model's resilience against adversarial attacks and data poisoning
B. Validate model code quality through peer review before merging to main branch
C. Compare a new candidate model's performance against the current production model before full deployment
Champion-challenger testing is used to run the incumbent production model (“champion”) alongside a proposed replacement (“challenger”) and measure whether the challenger improves the relevant metrics before any cutover. In deployment practice, the challenger is evaluated against the live baseline under the same operating conditions, so the decision point is whether it outperforms the current model sufficiently to justify promotion rather than being deployed blindly.
D. Ensure model documentation meets compliance requirements before deployment approval