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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 (Q47-Q52):

NEW QUESTION # 47
Which of the following should be done FIRST when an AI chatbot has been identified as giving harmful advice?

Answer: D

Explanation:
When a system is actively producing harmful content, the priority is " immediate containment. " " Enabling content output filters " is a critical safety control that acts as a " guardrail, " blocking the harmful responses before they reach the end-user. While prompt sanitization (Option A) targets the input , harmful advice often stems from the model ' s internal logic regardless of the input. Output filters provide the fastest mitigation for protecting users and the organization ' s reputation. Once the immediate risk is contained, the organization can conduct a root-cause analysis and perform more permanent retraining or access segmentation.


NEW QUESTION # 48
Which of the following will provide the BEST evidence to support the alignment of an AI model with an organization's business objectives?

Answer: C


NEW QUESTION # 49
The PRIMARY purpose of utilizing neural networks in AI is to:

Answer: C

Explanation:
Neural networks are designed to mimic the way the human brain processes information, enabling AI systems to identify complex patterns and make decisions based on data inputs. The AAIATM Study Guide defines neural networks as central to deep learning architectures that emulate cognitive functions.
"Neural networks simulate the interconnectivity and learning processes of the human brain. This capability enables AI systems to handle unstructured data and perform tasks such as image recognition, natural language processing, and predictive analytics."


NEW QUESTION # 50
An IS auditor reviewed an AI-enabled software for processing a bank's financial information and discovered errors in the training data. Which of the following would BEST mitigate this risk?

Answer: C

Explanation:
When errors are discovered in training data, the primary risk is that themodel has learned from incorrect or low-quality inputs, which can systematically distort outputs (e.g., misstatements of financial information, incorrect classifications, or erroneous flags).Data quality testingdirectly targets this issue by assessing completeness, accuracy, consistency, validity, and integrity of the data used to train, validate, and test AI models.
Functional testing (A) focuses on whether the application behaves according to requirements, not specifically on the underlying data quality. User interface testing (C) concerns usability and presentation, not training data. Model validation on benchmark data (D) helps assess performance but may not reveal or correct root# cause issues in the underlying training data if those benchmarks are also flawed or unrepresentative. AAIA content emphasizes thatdata quality controls are foundationalto AI reliability and must be treated as a core operational control.
References:
ISACA,Advanced in AI Audit (AAIA) Exam Content Outline- Domain 2: Data Management Specific to AI (data quality, data balancing, data security).
ISACA AI guidance on data quality controls as the basis of trustworthy AI outcomes.


NEW QUESTION # 51
When using off-the-shelf AI models, which of the following is the MOST appropriate way for organizations to approach vendor management?

Answer: B


NEW QUESTION # 52
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