AAIR AI Lifecycle Risk Management Practice Question
During the AI lifecycle, when should a 'Data Quality' assessment be performed to minimize long-term risk?
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
✓
During the data ingestion and preprocessing stage.
Data quality must be validated prior to training to ensure model reliability.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
After model deployment in production.
Why it's wrong here
Waiting until deployment is too late to prevent skewed model learning.
- ✗
During the final model sign-off.
Why it's wrong here
Sign-off is too late for corrective data action.
- ✗
During the decommission phase.
Why it's wrong here
Data quality is irrelevant once the model is retired.
- ✓
During the data ingestion and preprocessing stage.
Why this is correct
Performing quality checks before the model sees the data prevents propagation of errors into model weights.
About these practice questions
This AAIR question is part of Courseiva's 199-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.