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AI Risk Governance And Framework IntegrationhardMultiple ChoiceObjective-mapped

AAIR AI Risk Governance And Framework Integration Practice Question

An organization is using 'AI Model Monitoring' to track 'Concept Drift'. Why is this a risk governance issue?

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

It signals that the model's predictive accuracy is degrading due to changes in the data context.

Concept drift indicates that the model is no longer operating in the environment it was trained for, leading to inaccurate predictions and potential risk.

Answer analysis

Option-by-option breakdown

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

  • It indicates the model is running out of memory.

    Why it's wrong here

    Memory issues are infrastructure-related, not concept drift-related.

  • It is not a risk issue; it is a maintenance issue.

    Why it's wrong here

    Performance failure is a material risk.

  • It signals that the model's predictive accuracy is degrading due to changes in the data context.

    Why this is correct

    Drift is a performance risk that requires management intervention.

  • It shows that the model is 'thinking' too slowly.

    Why it's wrong here

    Latency is an performance issue, not drift.

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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

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