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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit (AAIA) Exam
Exam Number:AAIA
Exam Format:Multiple-choice, Remote proctoring or test center, Closed-book, Computer-based
Real Exam Qty:55
Passing Score:65%
Certificate Validity Period:Not publicly specified (requires ongoing CPE maintenance after certification)
Available Languages:English
Exam Duration:120 minutes
Exam Price:USD 459 (member), USD 599 (non-member)
Related Certifications:CPA
CIA
CISA
Recommended Training:Official AAIA Training Course Providers
ISACA AI Audit Training Resources
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
  • 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 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 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.

ISACA Advanced in AI Audit Sample Questions (Q62-Q67):

NEW QUESTION # 62
Which of the following BEST demonstrates effective coordination to ensure comprehensive oversight of an AI system deployed across multiple jurisdictions?

Answer: B

Explanation:
When AI systems span multiple jurisdictions, they are subject to different regulatory regimes, cultural expectations, and risk tolerances. AAIA emphasizes that oversight must be coordinated to avoid gaps or overlaps. Establishing joint oversight plans and communication channels between agencies (B) ensures that relevant authorities share information, align on expectations, and collectively monitor AI risks, enabling coherent and comprehensive oversight.


NEW QUESTION # 63
Which of the following is MOST important for an IS auditor to consider when identifying AI risk in a know your customer (KYC) application within a banking organization?

Answer: D

Explanation:
In high-stakes financial applications like KYC, the primary concern is the potential business and regulatory impact of an AI error-such as false customer rejection or failure to detect fraudulent accounts. The AAIA™ Study Guide emphasizes aligning AI risk assessments with business impact and regulatory exposure.
"In financial institutions, the most material risk of AI errors lies in operational disruption and regulatory fines.
KYC models must be assessed for how errors can lead to compliance failures or reputational harm." Benchmarking (B) supports best practice alignment, and incident response (C) is part of mitigation, but D addresses the most critical consequence of AI risks in banking.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Risk Impact and Business Alignment in AI Systems"


NEW QUESTION # 64
An IS auditor is auditing an AI system that predicts inventory needs. The system recently failed to predict a stock outage for a key product. Which of the following audit tests would BEST validate the system's accuracy?

Answer: A

Explanation:
The best way to validate the accuracy of a predictive AI system is to use historical testing with past sales data (option D). According to the AAIA™ Study Guide, "historical (or back-testing) is essential for evaluating how well a model would have performed using actual data from previous periods, directly reflecting its predictive validity." This method reveals any gaps or biases in the model by comparing predictions to known outcomes.
Unit testing, load testing, and sensitivity analysis are useful for technical verification and robustness but do not provide direct evidence of prediction accuracy in real-world scenarios.
Reference:ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Model Validation Techniques"


NEW QUESTION # 65
What is the MOST important reason government organizations should provide regular AI training programs for all staff?

Answer: D

Explanation:
Government organizations are held to high standards of transparency, fairness, and accountability. Regular AI training ensures that employees remainup-to-date on ethical responsibilities, legal implications, fairness obligations, and responsible AI principles(B). This aligns with AAIA's domain onethical and legal considerations, which stresses continuous competence-building.
Cost reduction (A) is not the primary driver. Understanding tools (C) is useful but not as critical as ethics.
Avoiding outdated information (D) is secondary. Ethics training is essential because government AI decisions affect public trust, rights, and equity.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Ethical AI Principles and Public-sector Obligations.


NEW QUESTION # 66
Which of the following provides the BEST evidence that an organization's AI integration is aligned with its overall technology strategy?

Answer: A

Explanation:
The BEST evidence of alignment between AI integration and technology strategy is thatclear KPIs(A) have been defined for AI systems and tied to strategic objectives, measurable outcomes, and governance oversight.
KPIs demonstrate that AI initiatives are monitored, performance is evaluated, and outcomes align with enterprise value.
Policies (B) are foundational but do not demonstrate strategic alignment. Innovation culture (C) is broad and subjective. AI expertise (D) indicates capability, not alignment. AAIA stresses linking AI outcomes to business goals throughmetrics, monitoring, and governance dashboards.
References:
ISACA,AAIA Exam Content Outline- Domain 1: AI Governance and Strategy Alignment.


NEW QUESTION # 67
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