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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Audit |
| Exam Number: | AAIA |
| Exam Format: | Scenario-based questions, Multiple-choice questions, Computer-based testing |
| Exam Duration: | 150 minutes |
| Certificate Validity Period: | 3 years |
| Passing Score: | 450 (scaled, range 200–800) |
| Available Languages: | Chinese, Spanish, English |
| Related Certifications: | ACCA CIA CISA CPA FCCA |
| Exam Price: | US$459 (member) / US$599 (non-member) |
| Real Exam Qty: | 90 |
| Recommended Training: | AAIA Official Review Course AAIA Review Manual |
| 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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NEW QUESTION # 159
An organization is reviewing its existing data governance framework after implementing an AI- based document repository solution. Which of the following should be the PRIMARY consideration?
Answer: C
Explanation:
The PRIMARY consideration is data classification (B), because the AI-based repository handles different types of documents that may contain sensitive, confidential, regulated, or public information. Proper classification ensures correct application of access controls, retention rules, encryption requirements, and privacy protections.
NEW QUESTION # 160
Which of the following data management practices poses the GREATEST risk to the reliability of an AI model ' s correlations?
Answer: D
Explanation:
While removing outliers can sometimes help with model performance, " Deleting outlier data values " arbitrarily poses the greatest risk to reliability because it can remove rare but legitimate data points that are critical for accurate pattern recognition. In domains like fraud detection or risk management, the outliers are the most important data. Distorting the natural distribution of data can lead to skewed correlations and a model that fails to recognize high-impact " tail " events. Encoding (Option B) and removing true duplicates (Option D) are standard, low-risk preprocessing steps. Correcting data types (Option C) is essential for enabling mathematical operations and is not a risk.
NEW QUESTION # 161
Which of the following initially provides assurance that the developer correctly interprets and identifies numerical data for balancing prior to inserting into the model?
Answer: B
Explanation:
Adata dictionary(A) is the authoritative source for understanding:
* Data types and numeric formats
* Valid ranges and interpretations
* Field definitions and business meaning
* Normalization and scaling expectations
Before balancing or preprocessing data, developers must verify that they understand each feature correctly.
The AAIA framework emphasizes thatmisinterpretation of numeric variablesoften leads to:
* Incorrect normalization
* Faulty scaling
* Skewed class balancing
* Inaccurate model training
Statistical summaries (C) help identify distributions but cannot validate semantic meaning. Confusion matrices (D) are used after training. Libraries (B) are tools, not sources of interpretation.
References:
AAIA Domain 2: Data Management - Data Dictionaries, Metadata, Data Understanding
NEW QUESTION # 162
Which of the following is the BEST use of AI to audit relationships for conflicts of interest or collusion?
Answer: D
Explanation:
Graph analytics is specifically designed to analyze complex relationships among people, entities, transactions, and systems. According to AAIA audit methodologies, graph analytics helps identify hidden or non-obvious relationships indicative of:
* Collusion
* Fraud rings
* Undisclosed conflicts of interest
* Influence networks
* Hidden ownership structures
Correlation matrices (A) only measure linear relationships. Time series (B) identifies patterns over time, not relationships. Monte Carlo simulation (D) models uncertainty but does not uncover relational structures.
Graph analytics is the strongest AI-enabled method for mapping and auditing relational risks.
References:
AAIA Domain 3: AI Tools for Audit Analytics
AAIA Domain 4: Relationship Analysis and Fraud Detection
NEW QUESTION # 163
Which of the following is the PRIMARY purpose of an AI acceptable use policy?
Answer: D
Explanation:
An AI acceptable use policy (AUP) defines how AI tools and technologies should be ethically and responsibly used within an organization. According to the AAIA™ Study Guide, the primary goal of an AUP is to prevent misuse and promote adherence to ethical, legal, and operational standards.
"An AI acceptable use policy provides governance over how AI tools may be used, especially regarding data handling, fairness, and prohibited uses. It aligns employee actions with organizational values and compliance requirements." Monitoring procedures (B), training (C), and taxonomy explanations (D) may be included in broader AI documentation, but the AUP's core purpose is ethical usage governance.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Policies, Standards, and Ethical Frameworks for AI"
NEW QUESTION # 164
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