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Pass Guaranteed AAIA - ISACA Advanced in AI Audit Useful New Practice Questions

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Pass Guaranteed 2026 Professional ISACA AAIA New Practice Questions

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ISACA Advanced in AI Audit Sample Questions (Q197-Q202):

NEW QUESTION # 197
Which of the following is the BEST way to mitigate data poisoning in an AI model?

A. Rely on external third-party model providers.
B. Implement robust data validation protocols.
C. Use simpler algorithms to improve explainability.
D. Increase training data set size.

Answer: B

Explanation:
Data poisoningoccurs when attackers manipulate training data to corrupt model behavior. The most direct mitigation is to implementrobust data validation and integrity checks(option C), including anomaly detection on input distributions, provenance controls, verification of data sources, and safeguards for pipelines feeding the training set. AAIA highlightsthreats and vulnerabilities specific to AIand the importance of controls that protect data integrity in AI Operations.
Option A (relying on third-party providers) does not inherently eliminate poisoning risk; providers themselves may be vulnerable. Option B (increasing data size) can dilute but not reliably remove malicious samples.
Option D (simpler algorithms) might help interpretability but does not directly prevent poisoned data from influencing the model. The most effective, aligned control isrigorous data validationto ensure only trustworthy data enters the training process.
References:
ISACA,AAIA Exam Content Outline- Domain 2: Threats and Vulnerabilities Specific to AI (controls for AI- related threats).
ISACA risk guidance referencing data integrity and poisoning risks in AI pipelines.

NEW QUESTION # 198
An IS auditor learns that an organization uses AI facial recognition technology for security purposes. Which of the following is the GREATEST ethical concern with this practice?

A. Absence of global standards for the use of AI in biometric security
B. Individuals beginning to interact more cautiously
C. Potential bias against certain demographic groups
D. Difficulty of enforcing access controls to facial recognition data

Answer: C

Explanation:
According to the ISACA AAIA™ Study Guide, facial recognition systems are prone to significant ethical risks related to fairness and bias. These systems often exhibit higher error rates for specific demographic groups-particularly based on race, gender, and age-due to non-representative training datasets. For an IS auditor, this represents a major compliance and reputational risk, as biased outcomes can lead to discriminatory access or false accusations. While data security (Option A) and the lack of standards (Option C) are relevant, the fundamental ethical imperative in AI governance is ensuring that biometric applications do not disproportionately disadvantage protected groups.

NEW QUESTION # 199
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?

A. Lack of procedures for automated data backup
B. Inconsistent data management practices
C. Limited frequency of AI system performance and data accuracy reviews
D. Inadequate controls over data accuracy and privacy compliance

Answer: D

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 # 200
Which of the following is the MOST important consideration when auditing the data used for training an AI model?

A. Understandability
B. Timeliness
C. Representativeness
D. Predictability

Answer: C

NEW QUESTION # 201
An IS auditor reviewing documentation for an AI model notes that the modeler utilized a K-means clustering algorithm, which clusters data into categories for correlations and analysis. Which of the following is the MOST important risk for the auditor to consider?

A. K-means clustering is not a common data clustering method due to its complexity and difficulty categorizing data correctly.
B. K-means clustering determines the number of clusters for the modeler without supervision.
C. K-means clustering requires the modeler to supervise the learning analysis, which can introduce bias.
D. K-means clustering algorithms are significantly sensitive to outliers and dependent on the similarity of units of measure.

Answer: D

NEW QUESTION # 202
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