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ISACA AAIA Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Governance and Risk33%- Privacy and Data Governance Programs
- AI Governance and Program Management
- Ethics, Regulations, and Standards for AI
- AI Models, Considerations, and Requirements
- AI Risk Management
Topic 2: AI Auditing Tools and Techniques21%- Audit Testing and Sampling Methodologies
- Data Quality and Analytics for AI Audit
- Audit Evidence Collection Techniques
- Audit Planning and Design
- AI Audit Outputs and Reporting
Topic 3: AI Operations46%- Incident Management and Resilience
- Performance Monitoring and Evaluation
- AI System Lifecycle and Deployment
- Operational Controls and Readiness
- Third-Party and Supply Chain Risk

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ISACA Advanced in AI Audit Sample Questions (Q194-Q199):

NEW QUESTION # 194
A healthcare AI tool recommends treatments with high success rates but significant risk. The hospital prioritizes patient safety over innovation. What is the BEST course of action?

Answer: C

Explanation:
AI systems must align with the organization's risk appetite and ethical principles, especially in healthcare where patient safety is paramount. The BEST action is to adjust the AI's parameters (A) so the recommendations reflect the hospital's conservative risk tolerance, reducing the frequency of high-risk suggestions. AAIA stresses AI governance alignment with organizational risk appetite, treatment guidelines, and ethical priorities.


NEW QUESTION # 195
Which of the following components would MOST effectively address cumulative benefits as part of reinforcement learning (RL)?

Answer: B

Explanation:
In Reinforcement Learning, the goal is to maximize long-term rewards. While the " Reward Function " provides immediate feedback for an action, the " Value Function " estimates the " cumulative benefit " or the total expected reward an agent can gain from a particular state moving forward. For an auditor, understanding the value function is crucial because it governs the agent ' s long-term strategy and decision-making logic. If the value function is poorly defined, the AI might take actions that yield immediate points but lead to long- term failure or unethical shortcuts.


NEW QUESTION # 196
Which of the following is MOST important to consider when auditing an organization's AI procedures?

Answer: D

Explanation:
The integrity of data fed into AI systems is a critical concern. The AAIATM Study Guide emphasizes that validation and filtration processes are essential to mitigate the risk of data poisoning--an attack that can manipulate model behavior by injecting malicious inputs.
"Data poisoning represents a major vulnerability in AI pipelines. Effective controls include robust validation, filtration, and monitoring of training data sources. These preventive practices are essential to ensure model reliability and security."


NEW QUESTION # 197
When reviewing contracts or other lengthy documentation in the planning phase, which of the following tools would BEST extract relevant information?

Answer: A

Explanation:
Natural Language Processing (NLP) enables systems to understand, summarize, and extract relevant insights from unstructured text data such as contracts, emails, or reports. The AAIA™ Study Guide recognizes NLP as the optimal tool for document review during audit planning or risk assessment phases.
"NLP techniques can efficiently process large volumes of documentation, highlight key clauses, and identify inconsistencies or risk indicators. This enhances audit productivity and thoroughness." While RPA (A) automates repetitive tasks, it doesn't interpret content. Predictive analytics (C) forecasts trends, and autoregressive models (B) generate sequences, not summarize documents.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "NLP Applications in Audit Planning and Risk Identification"


NEW QUESTION # 198
An IS auditor detected a "Prompt Injection" embedded in an email from a vendor that used an invisible font to hide text. Which of the following is the BEST control?

Answer: C

Explanation:
This is a "Hidden Text" attack, where an attacker tricks an LLM by embedding instructions that the human reader cannot see but the machine can process. The most effective "Incident Management" control is "Text Sanitization" that specifically strips out invisible formatting, hidden HTML tags, or zero-width characters before the text is sent to the AI.


NEW QUESTION # 199
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