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ISACA AAIA Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
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 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.

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ISACA Advanced in AI Audit Sample Questions (Q202-Q207):

NEW QUESTION # 202
An IS auditor is considering using a web-based AI tool to update an audit report. What should be the MOST important consideration before inputting the report?

Answer: D

Explanation:
The MOST important factor iscompliance with organizational data protection requirements(D), because audit reports contain sensitive internal information, findings, and potential control deficiencies. Sending such content to an external AI tool may result in data exposure or unauthorized processing. AAIA emphasizes privacy, confidentiality, and data protection obligationswhen interacting with external AI systems.
Option B (safeguards) is important but still secondary to ensuring compliance with internal data protection rules. Formatting alignment (A) and budget considerations (C) do not address the primary risk: improper disclosure of confidential audit data. Therefore,data protection complianceis the priority.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Legal, Privacy, and Ethical Considerations in AI.


NEW QUESTION # 203
Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

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 # 204
Which regulatory framework introduces a risk-tiered classification (unacceptable, high, limited, minimal) for AI systems?

Answer: B

Explanation:
The EU AI Act classifies AI systems into risk tiers, with high-risk systems subject to conformity assessments, documentation, and human oversight requirements.


NEW QUESTION # 205
Which of the following do supervised AI learning models PRIMARILY use to train algorithms?

Answer: C

Explanation:
Supervised learning is a foundational type of machine learning in which the model is trained on a labeled dataset. According to the AAIA™ Study Guide, labeled data includes input features along with the correct output, enabling the model to learn the mapping function accurately.
"In supervised learning, models learn from input-output pairs provided in the training data. This method enables predictive modeling tasks such as classification and regression." Unlabeled data (A) is used in unsupervised learning; clustered data (B) is a technique rather than a data type; and randomized data (D) refers to distribution strategy, not labeling. Hence, labeled data is the correct answer.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Fundamentals and Technologies," Subsection: "Types of AI Learning Models"


NEW QUESTION # 206
During a walk-through, an IS auditor observes an AI engineer entering a prompt that manipulates the AI model's behavior. Which of the following is the BEST control to prevent this?

Answer: A

Explanation:
The most direct and effective control for preventing prompt-based manipulation is to enforce a structured input/output template (option A). AAIA highlights prompt management as a key emerging control area because unstructured prompts can lead to:
Prompt injection
Model manipulation
Circumvention of rules
Unauthorized access to sensitive outputs
Safety violations
Templates constrain user input to predefined formats, reducing opportunities to embed hidden instructions or modify model behavior.


NEW QUESTION # 207
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