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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit
Exam Number:AAIA
Exam Price:US$459 (member) / US$599 (non-member)
Exam Format:Scenario-based questions, Multiple-choice questions, Computer-based testing
Real Exam Qty:90
Related Certifications:FCCA
CPA
CISA
ACCA
CIA
Available Languages:Spanish, English, Chinese
Passing Score:450 (scaled, range 200–800)
Certificate Validity Period:3 years
Exam Duration:150 minutes
Recommended Training:AAIA Review Manual
AAIA Official Review Course
Exam Registration:ISACA Official Registration
Sample Questions:ISACA AAIA Sample Questions
Exam Way:Computer-based; PSI test centers or remote proctored (remote not available in India, Mainland China, Hong Kong)
Pre Condition:Hold active CISA, CIA, CPA, ACCA, FCCA or equivalent qualified certification with IT audit/advisory focus
Official Syllabus URL:https://www.isaca.org/credentialing/aaia/aaia-exam-content-outline

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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
  • 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
  • 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.

ISACA Advanced in AI Audit Sample Questions (Q221-Q226):

NEW QUESTION # 221
Which control is MOST effective in reducing the risk of sensitive data being exposed through a large language model's outputs?

Answer: D

Explanation:
Limiting what sensitive data enters the model (minimization) and filtering outputs before they reach end users reduces the risk of inadvertent disclosure of PII or confidential data.


NEW QUESTION # 222
An IS auditor is reviewing AI-driven processes that automate financial approvals. Which of the following poses the GREATEST challenge to maintaining separation of duties (SOD)?

Answer: B

Explanation:
Separation of Duties (SOD) is intended to prevent errors or fraud by ensuring no single person (or entity) has control over all stages of a transaction. When AI automates financial approvals, the
"Lack of transparency in the algorithm" creates a challenge because the logic that grants approval is often opaque. If the algorithm functions as a "Black Box," it may consolidate decision- making power that was previously spread across multiple human roles, without sufficient visibility into how those decisions are made. This can lead to unauthorized or erroneous approvals going undetected. Effective AI governance must ensure that automated approvals are subject to transparent audit trails and secondary human reviews to uphold SOD principles.


NEW QUESTION # 223
A healthcare organization uses data clustering to group patients by medical history for personalized treatment recommendations. Which of the following is the GREATEST privacy risk associated with this practice?

Answer: B

Explanation:
Clustering, especially in sensitive domains like healthcare, can inadvertently expose confidential patient data if the resulting groups are too specific or reveal underlying health conditions. The AAIATM Study Guide warns that clustering can increase privacy risks when small, homogenous groups are formed that effectively re-identify individuals or reveal sensitive traits.
"Clustering results must be carefully reviewed to prevent indirect re-identification or unintended exposure of sensitive traits. Ethical handling of aggregated patient data is essential to protect individual privacy."


NEW QUESTION # 224
Which of the following controls MOST effectively helps to ensure an AI model is resilient against external threats?

Answer: A

Explanation:
Ensuring AI model resilience against external threats involves validating that the model is configured to resist attacks, such as adversarial inputs, data poisoning, or misuse. The AAIATM Study Guide emphasizes configuration testing as a crucial control to simulate threat scenarios and assess robustness.
"Model configuration testing simulates real-world threat conditions to validate model resilience.
This includes testing against adversarial attacks, input manipulation, and exposure of sensitive outputs." While access monitoring (C) and anonymization (A) reduce risks, they don't actively validate model behavior under threat conditions. Therefore, D offers the most effective resilience measure.


NEW QUESTION # 225
An IS auditor is reviewing the company ' s AI procedure. Which of the following would be the MOST critical gap?

Answer: C

Explanation:
AI governance requires a " Tiered Approach " based on risk. The most critical gap is the lack of " Mandatory Assessments " (such as Bias or Privacy Impact Assessments) for high-impact or critical systems. These assessments are the " Control Gates " that prevent the deployment of unsafe or unethical AI. While privacy principles (Option C) and oversight (Option D) are essential components, they are typically the outcome of the risk assessment process. Without a mandate to assess systems before they go live, the organization has no way to ensure that any of its other AI controls are being applied where they are most needed.


NEW QUESTION # 226
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