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ISACA AAIA Exam Syllabus Topics:

Topic	Details
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	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	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 (Q259-Q264):

NEW QUESTION # 259
During a walk-through, an IS auditor observes an AI engineer entering a prompt that manipulates the AI model's behavior. Which of the following is the BEST control to prevent this?

A. Retrain the model immediately
B. Enforce an input/output template
C. Encrypt the underlying data
D. Deploy adversarial training

Answer: B

Explanation:
The most direct and effective control for preventing prompt-based manipulation is toenforce a structured input/output template(option A). AAIA highlights prompt management as a key emerging control area because unstructured prompts can lead to:
* Prompt injection
* Model manipulation
* Circumvention of rules
* Unauthorized access to sensitive outputs
* Safety violations
Templates constrain user input to predefined formats, reducing opportunities to embed hidden instructions or modify model behavior.
Adversarial training (B) strengthens robustness but doesnotprevent users from inserting manipulative prompts.
Encryption (C) protects data, not prompt integrity.
Immediate retraining (D) addresses performance, not misuse.
Templates ensure consistent, secure, and auditable prompt structure.
References:
AAIA Domain 1: AI Governance, Prompt Controls
AAIA Domain 2: Security Controls for Generative AI

NEW QUESTION # 260
Which of the following metrics are the BEST indication of a mature and effective approach to an organization's data governance program for its AI systems?

A. Frequency of data quality audits on the organization's data sets
B. Percentage of AI models with documented data lineage
C. Number of AI projects completed within the last fiscal year
D. Total budget allocated to AI initiatives across all departments

Answer: B

NEW QUESTION # 261
Which of the following BEST helps an organization manage bias in AI model decisions?

A. Periodic model retraining
B. Standardization of fairness criteria
C. Human oversight and feedback mechanisms
D. Data anonymization and classification

Answer: C

Explanation:
Bias is often subtle and context-dependent, making it difficult for automated systems to detect on their own. " Human oversight and feedback mechanisms " (Human-in-the-loop) allow domain experts to review model decisions and flag outcomes that appear discriminatory or unfair. According to the AAIA™ framework, these human feedback loops are critical for " correcting " the model ' s logic over time. While standardizing criteria (Option A) is a good starting point, humans provide the necessary " common sense " and ethical judgment that machines lack. Retraining (Option D) without human-validated data may simply reinforce the existing biases rather than eliminate them.

NEW QUESTION # 262
An IS auditor is performing an inventory audit for a manufacturing organization. Which of the following would BEST enable the auditor to identify types of products without assistance from organizational staff?

A. Computer vision
B. Robotic process automation (RPA)
C. Speech modeling
D. Natural language processing

Answer: A

Explanation:
Computer vision uses machine learning techniques to identify and classify visual data such as images or videos. In inventory audits, it can be used to recognize product types, scan barcodes, or evaluate storage conditions without human assistance.
"Computer vision is particularly effective in automated environments like manufacturing, where visual data from cameras or sensors can be processed to verify product identification and placement." NLP (A) and speech modeling (B) are not suitable for image-based tasks. RPA (C) automates tasks but cannot visually interpret products. Therefore, D is the correct tool.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "AI Tools in Operational and Inventory Audits"

NEW QUESTION # 263
Which of the following should be an IS auditor's GREATEST concern when reviewing an anomaly detection process implemented for a high-risk AI system?

A. Inadequate staff training on the use of the system
B. Infrequent updates to anomaly detection algorithms
C. Failure to identify anomalies that can bias training data
D. Lack of regular quality reviews for training data

Answer: C

Explanation:
In a high-risk AI system, anomaly detection often serves as a frontline control to flag irregularities in input data and model behavior. The GREATEST concern for an IS auditor is when the process fails to identify anomalies that can bias training data (A), because undetected anomalies can fundamentally distort model learning and outputs. This can lead to systemic bias, incorrect decisions, safety risks, and regulatory breaches.

NEW QUESTION # 264
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