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ISACA AAIA Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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 (Q85-Q90):

NEW QUESTION # 85
Which of the following provides the BEST evidence that an organization's AI integration is aligned with its overall technology strategy?

A. The IT department includes many individual contributors with AI expertise.
B. Key performance indicators (KPIs) have been defined for AI systems.
C. The organization has developed and socialized AI use policies.
D. Management promotes a culture of innovation.

Answer: B

Explanation:
The BEST evidence of alignment between AI integration and technology strategy is that clear KPIs (A) have been defined for AI systems and tied to strategic objectives, measurable outcomes, and governance oversight. KPIs demonstrate that AI initiatives are monitored, performance is evaluated, and outcomes align with enterprise value.

NEW QUESTION # 86
Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

A. Comparing total food preparation and delivery time to an industry benchmark to set key performance and risk indicators for individual restaurants
B. Correlating time, cost, delivery distance, and customer satisfaction metrics to issue coupons to customers receiving substandard service
C. Using customer service metrics for service speed and food quality to predict customer retention and forecast revenue
D. Basing driver retention and termination decisions on the number of delivered orders per total hours worked as compared to an industry benchmark

Answer: D

Explanation:
Using AI to make employment decisions such as driver termination or retention introduces significant ethical risks. If based solely on performance metrics without context or human review, such systems can lead to unfair treatment or discrimination--violating principles of transparency and due process.
"Automating workforce decisions must be approached cautiously to prevent discriminatory outcomes. Ethical AI governance requires oversight when AI is used for employment-impacting decisions."

NEW QUESTION # 87
Which of the following is the MOST important purpose of conducting a risk assessment for AI models within an organization?

A. Determining whether AI model outputs align with established use cases
B. Defining mitigation strategies for AI deployment
C. Monitoring AI model performance on an ongoing basis
D. Categorizing data used by the AI model

Answer: B

Explanation:
Risk assessments identify potential threats and vulnerabilities in AI systems and support the development of mitigation strategies. According to the AAIATM Study Guide, the main objective is not just identification of risks but to proactively design controls that minimize impact and ensure ethical and regulatory compliance.
"The output of an AI risk assessment should lead to actionable mitigation strategies, supporting the secure and responsible deployment of AI solutions across business processes."

NEW QUESTION # 88
Which of the following is the GREATEST concern when an audit team relies on generative AI to create audit reports?

A. The reports may tend to use generic language for audit issues.
B. The reports may contain misstatements resulting from hallucinations.
C. The reports may use inconsistent formatting from prior audit findings.
D. The reports may be more likely to reflect outdated information.

Answer: B

Explanation:
The greatest concern is that the generative model may hallucinate, producing incorrect facts or conclusions (option B). In an audit context, hallucinations can create false statements about control effectiveness, misreport risks, or incorrectly summarize evidence.
AAIA stresses that auditors must maintain professional skepticism and validate AI-generated content. Misstatements are high-risk because they undermine audit credibility, regulatory compliance, and organizational decision-making.

NEW QUESTION # 89
Which of the following BEST describes "human-in-the-loop" as an AI control?

A. A human periodically audits the training data
B. A human writes the model's code
C. A human reviews and can override AI-generated decisions before they take effect
D. A human trains new employees on the AI system

Answer: C

Explanation:
Human-in-the-loop controls insert human judgment at the decision point, particularly for high-risk or high-impact outputs, serving as a safeguard against automation errors.

NEW QUESTION # 90
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