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ISACA Advanced in AI Security Management Questions 106–110 (page: 23)

Updated On: 13-Sep-2026

Which of the following is the MOST critical success factor for an AI implementation project?

  1. Mapping data throughout the life cycle
  2. Obtaining senior management buy-in
  3. Ensuring AI risk is captured in the risk register
  4. Developing and using model cards

Answer(s): B

Explanation:

Senior management buy-in is the most critical success factor because it ensures strategic alignment, funding, governance authority, and organizational support necessary for successful AI implementation.



An organization is planning to commission a third-party AI system to make decisions using sensitive data.
Which of the following metrics is MOST important for the organization to consider?

  1. Accessibility rating
  2. Model response time
  3. Accuracy thresholds
  4. Service availability

Answer(s): C

Explanation:

Accuracy thresholds are most important because decisions made using sensitive data must be reliable and correct to prevent harm, regulatory violations, and loss of trust.



Which AI model is BEST suited to ensure explainability in an HR department's pre-screening tool for candidate resumes?

  1. Support vector machine
  2. Neural network
  3. Decision tree
  4. Gradient boosting machine

Answer(s): C

Explanation:

Decision trees provide clear, human-readable decision paths that make it easy to understand why a candidate was screened in or out, which is essential for explainability and transparency in HR pre-screening decisions.



Which of the following is the MOST effective way to prevent a model inversion attack?

  1. Monitor model output for anomalous patterns.
  2. Utilize data pseudonymization techniques.
  3. Implement differential privacy during model training.
  4. Ensure data minimization best practices.

Answer(s): C

Explanation:

Differential privacy during model training limits the amount of information the model can reveal about individual training records, effectively preventing attackers from reconstructing sensitive data through model inversion techniques.



The PRIMARY purpose of adopting and implementing AI architecture as part of an organizational AI program is to:

  1. deploy fast and cost-efficient AI systems for rapidly changing environments.
  2. provide a basis for identification of threats and vulnerabilities.
  3. align the system components of AI with the business goals of the organization.
  4. ensure the development of powerful, efficient, and scalable AI systems.

Answer(s): C

Explanation:

AI architecture primarily serves to align AI system components, data flows, and capabilities with the organization’s business goals, ensuring that AI initiatives deliver intended value while supporting governance, risk management, and strategic objectives.



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