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NEW QUESTION # 32
Which of the following is the GREATEST risk associated with deploying an AI system with ineffective anomaly detection?
Answer: A
Explanation:
Ineffective anomaly detection means the system fails to recognize abnormal patterns in data or model behavior. The GREATEST risk isundetected data poisoning(B), which jeopardizesdata integrityand leads to corrupted, biased, or unsafe AI decisions. AAIA emphasizes that anomaly detection is critical for identifying tampering, data drift, or malicious manipulation.
Configuration inconsistencies (A) are operational issues but far less damaging. Slower drift response (C) can cause performance degradation but is not as severe as undetected poisoning. Reporting standard failures (D) are compliance risks-not as critical as compromised decision integrity.
Thus, undetected poisoning poses thehighest riskdue to its direct impact on model trustworthiness and safety.
References:
ISACA,AAIA Exam Content Outline- Domain 2: AI Operations; Threats and Vulnerabilities in AI.
NEW QUESTION # 33
An IS auditor finds that an AI model's outputs are not being reviewed. Which of the following would BEST address this risk?
Answer: B
Explanation:
WhenAI outputs are not being reviewed, the primary concern is thatincorrect, biased, or non-compliant decisionsmay go undetected. The best way to address this risk is to implement avalidation process for AI decisions(B), which may include human-in-the-loop checks, sampling-based reviews, escalation criteria, and formal approval workflows. AAIA emphasizes the importance ofsupervision and validation of AI outputs, particularly where decisions have financial, legal, or safety implications.
A larger training dataset (A) does not guarantee correctness or fairness and does not replace oversight.
Regular retraining (C) can be beneficial but can also propagate errors if not validated. Prompt templates (D) are relevant mainly for generative and prompt-based systems, and they do not constitute systematic review of outputs. Therefore, astructured validation processis the most direct and effective control.
References:
ISACA,AAIA Exam Content Outline- Domain 2: AI Operations (Supervision of AI Solutions).
ISACA audit guidance on AI decision validation and human oversight.
NEW QUESTION # 34
Which role is BEST suited to define the implementation roadmaps for adopting AI solutions?
Answer: C
Explanation:
A steering committee is responsible for enterprise-wide strategic decisions, technology alignment, investment prioritization, and governance oversight.
AAIA states that AI implementation roadmaps must be driven by a group that can evaluate:
* Organizational strategy
* Technology readiness
* Budget allocations
* Risk appetite
* Regulatory obligations
* Cross-functional impacts
The risk committee (A) focuses only on risk, not implementation. Product management (C) has a narrow scope. Internal audit (D) evaluates controls, not roadmaps.
Thus, the steering committee is the appropriate authority.
References:
AAIA Domain 1: AI Governance Structures
AAIA Domain 4: Strategic Alignment and Oversight
NEW QUESTION # 35
An IS auditor reviewed an AI-enabled software for processing a bank's financial information and discovered errors in the training data. Which of the following would BEST mitigate this risk?
Answer: D
Explanation:
When errors are discovered in training data, the primary risk is that the model has learned from incorrect or low-quality inputs, which can systematically distort outputs (e.g., misstatements of financial information, incorrect classifications, or erroneous flags). Data quality testing directly targets this issue by assessing completeness, accuracy, consistency, validity, and integrity of the data used to train, validate, and test AI models.
NEW QUESTION # 36
Which of the following is the MOST effective control to safeguard a model's architecture, weights, and hyperparameters?
Answer: B
Explanation:
The most effective way to protect proprietary AI model components--architecture, weights, hyperparameters--is through strict access controls and encryption (option D).
AAIA identifies model theft and reverse engineering as high-severity security risks, especially for organizations whose competitive advantage relies on intellectual property embedded in AI models.
Proper controls include:
Role-based access control (RBAC)
Encryption at rest and in transit
Model-level access segregation
Hardware security modules (HSMs)
Zero-trust access principles
NEW QUESTION # 37
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