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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 (Q17-Q22):

NEW QUESTION # 17
An organization's AI model relies on synthetic data to augment a small training dataset. What is the PRIMARY audit consideration?

Answer: A

Explanation:
Synthetic data generation methods can inadvertently encode or amplify biases present in the seed data, or fail to capture rare real-world scenarios, undermining model reliability if not properly validated.


NEW QUESTION # 18
Which of the following controls would MOST effectively mitigate worst-case service disruption scenarios affecting an AI-based application system?

Answer: A

Explanation:
Including AI-specific disruption scenarios in the organization's Disaster Recovery Plan (DRP) ensures preparedness for worst-case events affecting AI systems. The AAIA™ Study Guide recommends tailoring business continuity and DR strategies to cover model unavailability, data corruption, and AI-specific dependencies.
"AI disruptions can arise from unique causes such as model corruption, adversarial attacks, or drift.
Integrating these into the DRP allows for effective, scenario-specific responses and minimizes downtime." Tabletop exercises (A) are valuable for preparedness but are less comprehensive than scenario planning. Kill chains (B) are security-specific. KRIs (C) aid in monitoring but don't ensure recovery. Therefore, D offers the most robust mitigation.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Business Continuity and Disaster Recovery Planning for AI"


NEW QUESTION # 19
An auditor notes that a model's decision threshold was changed by a developer without documentation or approval. What control failure does this represent?

Answer: B

Explanation:
Any modification to a production model's parameters -- including thresholds -- should go through a formal change management process with approval and documentation, regardless of how minor it appears.


NEW QUESTION # 20
An organization is developing an AI system that integrates data from multiple external sources without clearly defined data ownership policies. Which of the following is the GREATEST concern in this situation?

Answer: C

Explanation:
When integrating data from multiple external sources, unclear data ownership directly affects accountability for privacy, consent, retention, and lawful processing. This creates gaps in AI privacy compliance and accountability (option D), which is the greatest concern because violations can lead to regulatory sanctions, litigation, and serious reputational damage. AAIA's governance and risk domain emphasizes privacy and data governance programs, including clear roles, responsibilities, and ownership.


NEW QUESTION # 21
An organization shares an AI model with external partners. One partner reports that sensitive data has been inadvertently exposed through the model's outputs. Which of the following is the IS auditor's BEST recommendation?

Answer: B

Explanation:
In the case of a potential data exposure through AI model outputs, the first and most responsible action from an auditing and risk standpoint is to halt further risk propagation. According to the AAIATM Study Guide, immediate containment is vital, especially when regulatory and reputational risks are high.
"Upon detection of a data breach risk, AI models should be immediately disabled from public or partner use, and all relevant parties should be notified as part of a responsible disclosure and containment strategy."


NEW QUESTION # 22
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