AAIA AI Governance And Risk Practice Question
When auditing an AI system for regulatory compliance, you find that data lineage is broken between the feature store and the training pipeline. Which control is most likely deficient?
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
✓
Metadata logging and transformation documentation
Feature stores must maintain end-to-end traceability to ensure that data provenance is clear and auditable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Access control lists for the model production environment
Why it's wrong here
Access controls manage security, not the logical lineage of data transformations.
- ✗
Encryption of data at rest in the data warehouse
Why it's wrong here
Encryption protects data confidentiality, not its operational lineage.
- ✗
Load balancing configuration for the inference API
Why it's wrong here
Load balancing is an infrastructure reliability configuration, not a data provenance control.
- ✓
Metadata logging and transformation documentation
Why this is correct
Metadata is the key to maintaining lineage; without it, the link between features and training data is obscured.
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 AAIA 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 AAIA exam.