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ISACA AAIA Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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.

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ISACA Advanced in AI Audit Sample Questions (Q70-Q75):

NEW QUESTION # 70
Which of the following is the PRIMARY objective of AI governance?

Answer: B

Explanation:
The AAIA™ Study Guide defines the primary objective of AI governance as establishing structure and accountability for AI initiatives. This includes clearly assigning responsibilities across development, deployment, risk management, and auditing roles to ensure that AI is used responsibly and transparently.
"AI governance establishes the policies, roles, and oversight structures that guide the ethical and secure deployment of AI. Clear accountability helps prevent unauthorized use and ensures strategic alignment." Options A and C are essential components of governance but are not its core definition. Option D is a business outcome, not a governance goal. Thus, B is the most comprehensive and accurate objective.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Governance Objectives and Structures"


NEW QUESTION # 71
An IS auditor analyzed an AI model scorecard and identified that training data was imbalanced.
Which of the following is the BEST recommendation to remediate risk?

Answer: D

Explanation:
Data imbalance (where one class significantly outweighs another) leads to biased models that perform poorly on minority classes. The ISACA AAIATM manual suggests that "class-weighted loss" is a proactive technical control that penalizes the model more for misclassifying minority samples, effectively "balancing" the learning process. Stratified splitting ensures that every training and validation set maintains the same ratio of classes as the original data, preventing the model from failing to "see" minority cases during the testing phase.


NEW QUESTION # 72
An organization is adopting AI for its procurement and inventory teams, raising concern from stakeholders that they will lose their jobs due to AI. Which of the following is the BEST way for the IS auditor to assess whether the potential negative impacts were minimized?

Answer: C

Explanation:
Human-centered design (HCD) focuses on integrating stakeholder needs, ethical implications, and social impact into AI system development. The AAIATM Study Guide emphasizes the role of HCD in minimizing negative workforce impacts and ensuring inclusive design.
"Auditors should review whether the AI system design process included human-centered practices-- particularly for applications affecting jobs or critical human roles. HCD ensures responsible adoption."


NEW QUESTION # 73
An organization deployed an AI-powered customer service chatbot trained using customer chat logs. During a risk assessment, which issue should be the IS auditor's GREATEST concern?

Answer: D

Explanation:
The GREATEST concern isinsufficient access controls(D), which can lead tounauthorized exposure of customer data-a severe privacy, security, regulatory, and reputational risk. Chat logs often contain personally identifiable information and sensitive communications. AAIA prioritizesdata confidentiality, access control, and privacy obligationsas highest-risk elements, particularly for customer-interactive AI systems.
Inaccurate chatbot responses (C) affect reputation but are less severe than data breaches. Obsolete procedures (B) matter but pose less immediate harm. Limited capability to incorporate data (A) affects performance but not critical risk.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Legal and Privacy Considerations; Domain 1: AI Governance and Security Controls.


NEW QUESTION # 74
An organization is using information gathered from customer accounts to train its AI chatbot. Which of the following is the GREATEST risk associated with this practice?

Answer: A

Explanation:
The use of customer data in AI training presents a significant privacy risk, especially when the data is not properly anonymized or when consent has not been explicitly obtained. The AAIA™ Study Guide classifies the unauthorized or inadvertent disclosure of personally identifiable information (PII) as the most severe risk in such contexts.
"Training AI models on customer data without proper safeguards can result in the unintentional exposure of personal or sensitive information, leading to data breaches and compliance violations." While bias (B) and hallucinations (D) are important operational concerns, they do not pose the same regulatory and ethical severity as PII exposure. Therefore, A is the most critical risk.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Privacy Risks and Data Minimization"


NEW QUESTION # 75
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