AAIR AI Risk Program Management Practice Question
When defining KPIs for an AI Governance program, which metric is most predictive of long-term model robustness?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The frequency of model retraining triggered by performance drift alerts.
Model drift and retraining frequency serve as leading indicators for the degradation of AI reliability over time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Number of users accessing the AI interface.
Why it's wrong here
Usage volume indicates adoption, not the robustness of the AI model.
- ✓
The frequency of model retraining triggered by performance drift alerts.
Why this is correct
Retraining frequency related to drift is a direct indicator of whether a model remains robust in a changing environment.
- ✗
Total number of AI models currently in production.
Why it's wrong here
Inventory size does not indicate the quality or risk level of the models.
- ✗
The budget spent on GPU cloud computing resources.
Why it's wrong here
Spend is an operational metric, not a risk-specific KPI.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official ISACA exam blueprint
This AAIR practice question is part of Courseiva's free ISACA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AAIR exam.