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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)
Real Exam Qty:90
Exam Duration:150 minutes
Passing Score:450 (scaled, range 200–800)
Exam Format:Computer-based testing, Scenario-based questions, Multiple-choice questions
Related Certifications:ACCA
FCCA
CIA
CPA
CISA
Available Languages:Chinese, English, Spanish
Certificate Validity Period:3 years
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
  • 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 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
  • 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 (Q37-Q42):

NEW QUESTION # 37
A bank is deploying an AI model trained on customer transactions in a multi-cloud environment. Which of the following BEST supports regulatory compliance regarding data security and privacy?

Answer: A

Explanation:
In a multi-cloud environment, data often traverses various geographical regions. For financial institutions, " Data residency and sovereignty " are the most critical compliance factors, ensuring that data is stored and processed within the jurisdictions required by law (e.g., GDPR or local banking acts). Failure to control where data resides can lead to severe legal penalties. While " Privacy by Design " and " DPIA " are essential methodologies, they do not specifically address the physical and legal location of data across cloud providers.
Sovereignty controls ensure the bank maintains control over its data assets and complies with specific cross- border data transfer regulations.


NEW QUESTION # 38
An IS auditor reviewing the latest AI chatbot release identifies that, despite high accuracy rates, non-English users complain about the model's poor accuracy. Which of the following controls is BEST at ensuring detection of subgroup regressions?

Answer: D

Explanation:
A common pitfall in AI performance is "aggregate accuracy," which masks poor performance in specific demographics or subgroups. To detect these "subgroup regressions," auditors should look for "comparative evaluations" where the model is tested separately for different languages.
"Parity thresholds" establish the maximum allowable difference in performance between the majority group (English) and minority groups. This ensures fairness and consistent user experience. Post-go-live human review is reactive, and translating everything to English ignores the nuances of the original language that likely caused the errors in the first place.


NEW QUESTION # 39
Which of the following is the BEST way to support the development and design of high-risk AI systems?

Answer: A


NEW QUESTION # 40
An AI-based marketing analytics tool is trained on data that is five years old. Which of the following is MOST likely to occur?

Answer: B

Explanation:
Model drift (also called concept drift) occurs when the data used for training no longer reflects the current environment. In marketing, consumer behaviors, trends, and demographics change rapidly; therefore, a model trained on five-year-old data will suffer from significant drift. The AAIATM manual explains that this results in the model making predictions based on obsolete patterns, leading to poor accuracy and potentially biased or irrelevant marketing recommendations.


NEW QUESTION # 41
Which of the following is the PRIMARY benefit of implementing a robust data governance framework specific to AI solutions in an organization?

Answer: C


NEW QUESTION # 42
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