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ISACA AAIA Questions - Get Success In First Attempt (2025)

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ISACA AAIA Exam Syllabus Topics:

Topic
Details

Topic 1

Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.

Topic 2

AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.

Topic 3

AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.

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ISACA Advanced in AI Audit Sample Questions (Q12-Q17):

NEW QUESTION # 12
When utilizing a machine learning (ML) model to predict whether a wind turbine electricity generator will fail, which model evaluation metric should be the PRIMARY focus?

A. Accuracy
B. Specificity
C. Precision
D. Recall

Answer: D

NEW QUESTION # 13
While evaluating a complex machine learning (ML) model used for regulatory compliance in a financial institution, which of the following should the IS auditor do to BEST ensure transparency?

A. Create dashboards to show outputs.
B. Document sources and data processes.
C. Use tools that explain model decisions.
D. Provide periodic model audit reports.

Answer: C

NEW QUESTION # 14
The PRIMARY objective of machine learning (ML) in data processing is to:

A. Draw statistical inferences for creating artificial human intelligence.
B. Perform actions that would typically require human intelligence.
C. Enhance the explainability of AI model outputs.
D. Analyze data sets to identify visual patterns and trends.

Answer: B

NEW QUESTION # 15
Which of the following is the PRIMARY reason IS auditors must be aware that generative AI may return different investment recommendations from the same set of data?

A. Servers are reconfigured periodically.
B. Computational logic is based on probabilities.
C. Limitations can arise in the quantification of risk profiles.
D. Neural node access varies each time the process is executed.

Answer: B

NEW QUESTION # 16
Which of the following is the GREATEST challenge facing IS auditors evaluating the explainability of generative AI models?

A. Differences of opinion regarding model types
B. Difficulties in preventing the input of biased data
C. Performance issues due to excessive computation
D. Algorithms changing as AI continues to learn

Answer: D

NEW QUESTION # 17
......

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