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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit (AAIA) Exam
Exam Number:AAIA
Related Certifications:CIA
CPA
CISA
Available Languages:English
Passing Score:65%
Exam Format:Remote proctoring or test center, Closed-book, Computer-based, Multiple-choice
Certificate Validity Period:Not publicly specified (requires ongoing CPE maintenance after certification)
Exam Price:USD 459 (member), USD 599 (non-member)
Real Exam Qty:55
Exam Duration:120 minutes
Recommended Training:ISACA AI Audit Training Resources
Official AAIA Training Course Providers
Exam Registration:ISACA AAIA Certification Page
Sample Questions:ISACA AAIA Sample Questions
Exam Way:Computer-based exam delivered via PSI test centers or remote proctoring
Pre Condition:Must hold an active CISA, CIA, CPA, or equivalent ISACA-approved advanced auditing certification
Official Syllabus URL:https://www.isaca.org/credentialing/aaia

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ISACA AAIA Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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.

ISACA Advanced in AI Audit Sample Questions (Q319-Q324):

NEW QUESTION # 319
An IS auditor is evaluating an organization's data governance controls for its AI system. Which of the following represents the GREATEST risk in this context?

Answer: B

Explanation:
In AI systems,data accuracy and privacyare foundational to both performance and regulatory compliance.
Inadequate controls over data accuracy and privacy compliance(D) pose thegreatest risk, as they can lead to incorrect decisions, legal violations, regulatory penalties, and significant reputational damage. AAIA emphasizes that data governance programs must ensure data is accurate, secure, lawfully processed, and appropriately protected throughout the AI life cycle.
Option A (inconsistent practices) is concerning but is often a symptom of underlying governance weaknesses; its impact is most severe when it affects accuracy and privacy. Option B focuses on backup procedures, which are important for availability and resilience, but not as central to AI decision quality and legal risk. Option C (limited performance and accuracy reviews) is serious but again narrower than outright inadequacy of key controls over accuracy and privacy.
References:
ISACA,AAIA Exam Content Outline- Domain 1: Privacy and Data Governance Programs (accuracy, privacy, and governance controls).
ISACA data governance and privacy guidance for AI systems.


NEW QUESTION # 320
A manufacturing company installs an AI system to control robotic arms on its assembly line. The system learns over time, adjusting its movements based on production results to improve accuracy. What type of learning is the robot MOST likely using?

Answer: A

Explanation:
Reinforcement Learning (RL) is characterized by an "agent" (the robot) that learns to achieve a goal in a dynamic environment through trial and error. It receives "rewards" for correct movements and "penalties" for errors, allowing it to optimize its "Policy Function" over time.


NEW QUESTION # 321
Which of the following is the GREATEST risk associated with deploying an AI system with ineffective anomaly detection?

Answer: C

Explanation:
Ineffective anomaly detection means the system fails to recognize abnormal patterns in data or model behavior. The GREATEST risk isundetected data poisoning(B), which jeopardizesdata integrityand leads to corrupted, biased, or unsafe AI decisions. AAIA emphasizes that anomaly detection is critical for identifying tampering, data drift, or malicious manipulation.
Configuration inconsistencies (A) are operational issues but far less damaging. Slower drift response (C) can cause performance degradation but is not as severe as undetected poisoning. Reporting standard failures (D) are compliance risks-not as critical as compromised decision integrity.
Thus, undetected poisoning poses thehighest riskdue to its direct impact on model trustworthiness and safety.
References:
ISACA,AAIA Exam Content Outline- Domain 2: AI Operations; Threats and Vulnerabilities in AI.


NEW QUESTION # 322
An organization is using information gathered from customer accounts to train its AI chatbot. Which of the following is the GREATEST risk associated with this practice?

Answer: A

Explanation:
The use of customer data in AI training presents a significant privacy risk, especially when the data is not properly anonymized or when consent has not been explicitly obtained. The AAIA™ Study Guide classifies the unauthorized or inadvertent disclosure of personally identifiable information (PII) as the most severe risk in such contexts.
"Training AI models on customer data without proper safeguards can result in the unintentional exposure of personal or sensitive information, leading to data breaches and compliance violations." While bias (B) and hallucinations (D) are important operational concerns, they do not pose the same regulatory and ethical severity as PII exposure. Therefore, A is the most critical risk.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Privacy Risks and Data Minimization"


NEW QUESTION # 323
When auditing an AI system, which of the following steps ensures that AI model behavior is aligned with organizational objectives?

Answer: A

Explanation:
Problem framing (option D) is the process of clearly defining the purpose, scope, and desired outcomes of an AI system before it is built or deployed. According to the ISACA AAIATM Study Guide, "problem framing is the critical first step that aligns model development and subsequent behaviors with the strategic and operational objectives of the organization." If the AI problem is not framed in accordance with organizational goals, even a technically successful AI model could generate outputs that do not support the organization's mission or priorities.
Algorithm debugging, data transformation, and model training are all important phases but rely on the initial problem framing to ensure their efforts are correctly directed.


NEW QUESTION # 324
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