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AAIA AI Governance And Risk Practice Question

Which technique is most appropriate for mitigating 'Concept Drift' in a production model?

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

Implementing an automated re-training pipeline based on performance threshold triggers

Continuous re-training or fine-tuning based on recent data is the standard mitigation for concept drift.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increasing the number of neurons in the hidden layers

    Why it's wrong here

    Adding capacity doesn't solve drift; it just makes the model more complex.

  • Moving the model to a larger GPU cluster

    Why it's wrong here

    Infrastructure upgrades don't fix the underlying statistical issue of concept drift.

  • Implementing an automated re-training pipeline based on performance threshold triggers

    Why this is correct

    Automated re-training using recent, representative data corrects the drift in the model's concept.

  • Restricting access to the training dataset

    Why it's wrong here

    Access restriction is a security control, not a drift mitigation tactic.

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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.