AAIR AI Risk Program Management Practice Question
An organization is updating its risk appetite statement for AI. Which specific element should be addressed to manage the 'hallucination' risk of LLMs?
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
✓
Require human-in-the-loop for any AI-generated output used in customer-facing content.
Establishing clear boundaries for where generative AI is acceptable versus prohibited is a key aspect of risk appetite.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set a performance goal to reduce the model parameter count.
Why it's wrong here
Model size is not the primary factor in managing hallucination risk.
- ✓
Require human-in-the-loop for any AI-generated output used in customer-facing content.
Why this is correct
Human-in-the-loop is the primary control for mitigating the impact of generative AI hallucinations.
- ✗
Increase the frequency of periodic penetration testing.
Why it's wrong here
Penetration testing is for security, not output quality or veracity.
- ✗
Limit the training dataset to under 10GB.
Why it's wrong here
Dataset size does not correlate directly with hallucination risk.
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.