AAISM AI Technologies And Controls Practice Question
When training an AI model, why is it critical to ensure 'Data Provenance'?
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
✓
To verify the source and integrity of training data
Data provenance allows auditors to trace the origin of data, ensuring no poisoned or copyrighted data entered the training pipeline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
To verify the source and integrity of training data
Why this is correct
Provenance is foundational to data supply chain security.
- ✗
To reduce the storage space of datasets
Why it's wrong here
Provenance is about record-keeping, not storage.
- ✗
To automatically remove PII from datasets
Why it's wrong here
Provenance identifies sources; cleaning is a different step.
- ✗
To optimize the training speed of the model
Why it's wrong here
Provenance is about security, not speed.
About these practice questions
This AAISM question is part of Courseiva's 205-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 AAISM 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 AAISM exam.