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ISACA AAIA Exam Syllabus Topics:

TopicDetails
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 (Q235-Q240):

NEW QUESTION # 235
Which of the following techniques BEST enhances the security and robustness of AI models against adversarial attacks?

Answer: C

Explanation:
Defensive distillation is a specialized technique designed to make an AI model more robust against adversarial " perturbations " -small changes to input data intended to trick the model. It works by training a smaller model to mimic the probability distributions of a larger, pre-trained model, which effectively " smooths " the decision boundaries and makes it harder for attackers to find exploitable gaps. While access reviews and awareness training are standard security controls, they do not address the mathematical vulnerabilities inherent in ML algorithms. Defensive distillation specifically targets the model ' s resilience to technical exploitation.


NEW QUESTION # 236
Which of the following is the BEST recommendation to mitigate excessive agency when implementing an AI system as a browser extension?

Answer: A

Explanation:
Excessive agency occurs when AI systems act too autonomously, making decisions without appropriate human oversight. To mitigate this in a browser extension, the BEST approach is to minimize functionality (A), ensuring the extension performs only narrowly defined, controlled actions. This aligns with AAIA's guidance on limiting AI autonomy, applying least-privilege principles, and restricting unnecessary actions.


NEW QUESTION # 237
An organization utilizes an off-the-shelf generative AI solution for internal business processing.
According to the principle of shared responsibility, which of the following areas remains the PRIMARY responsibility of the organization?

Answer: D

Explanation:
In a "Software as a Service" (SaaS) or off-the-shelf AI model deployment, the "Shared Responsibility Model" dictates that the vendor is responsible for the "Security OF the model" (infrastructure, base training, core safety), while the customer is responsible for the "Security IN the model" (usage). The organization's primary duty is "Defining usage policies and enforcing IAM" to ensure that only authorized employees use the tool and that they do not input sensitive corporate data into unvetted prompts. This governance ensures the AI is used ethically and securely within the organization's specific operational context.


NEW QUESTION # 238
When an IS auditor uses generative AI with external RAG (retrieval-augmented generation) to gather evidence during an audit, which of the following poses the GREATEST data security risk?

Answer: B

Explanation:
The GREATEST risk is that sensitive internal content may be embedded in AI prompts and sent to an external system (A), exposing confidential or regulated information. Retrieval-augmented generation often involves sending queries or embeddings to third-party APIs, creating a significant data leakage risk if internal context is included.


NEW QUESTION # 239
An IS auditor is looking to expedite reporting for an audit with complex issues. Which of the following would be the MOST effective way for the auditor to use generative AI?

Answer: B

Explanation:
The AAIA™ Study Guide highlights that generative AI tools can significantly enhance audit productivity, especially in content generation tasks. Drafting executive summaries-condensing complex findings into clear, concise formats-is a high-impact use case that benefits from generative AI's natural language generation capabilities.
"Generative AI can be leveraged by auditors to automate reporting sections, such as executive summaries, ensuring consistency and saving time without compromising content clarity." While A, C, and D are valid uses, B delivers the most value by expediting a time-intensive and high-level reporting task in complex audits.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "Generative AI Applications in Audit Reporting"


NEW QUESTION # 240
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