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The web-based ISACA AAIA practice exam is compatible with all browsers like Chrome, Mozilla Firefox, MS Edge, Internet Explorer, Safari, Opera, and more. Unlike the desktop version, it requires an internet connection. The ISACA Advanced in AI Audit (AAIA) practice exam will ask real ISACA Advanced in AI Audit (AAIA) exam questions. Consistent practice with it relieves exam stress and boosts self-confidence. The web-based ISACA Advanced in AI Audit (AAIA) practice exam does not require additional software installation. All operating systems also support this ISACA Advanced in AI Audit (AAIA) practice test.
NEW QUESTION # 213
Which of the following insider threats involving the use of AI would present the GREATEST risk?
Answer: D
Explanation:
The GREATEST insider threat isexfiltrating sensitive data(D). AI systems often contain rich datasets including personal, financial, operational, and proprietary information. If an insider extracts or leaks this data, the result can be severe legal, regulatory, and reputational consequences.
Destroying backups (C) affects availability but not confidentiality. Social engineering attacks (B) are serious but indirect. Hyperparameter leakage (A) exposes model configuration but usually does not endanger sensitive data directly. AAIA stresses thatdata confidentiality risksare the most severe category in AI governance.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Ethical and Legal Risks; Data Protection and Confidentiality.
NEW QUESTION # 214
An internal audit department notices that AI-generated audit reports are producing false conclusions. Which of the following is the BEST way to correct this issue?
Answer: D
Explanation:
If AI-generated audit reports contain false conclusions, the integrity of audit evidence and overall assurance is compromised. According to AAIA, when AI systems compromise accuracy of audit outputs, the immediate step should be to suspend use (B) to prevent further incorrect or misleading reporting.
This allows auditors to:
Investigate the root cause of incorrect conclusions
Validate the model's training data, rules, and prompt structures
Reassess controls, safeguards, and human review processes
Prevent reliance on unreliable AI-generated audit material
NEW QUESTION # 215
An IS auditor is assessing the implementation of AI tools for evidence collection involving multiple data sources. Which of the following outcomes BEST indicates that AI-driven evidence collection has improved the audit process?
Answer: A
Explanation:
AI-driven evidence collection should enhanceefficiency and accuracy. The BEST indicator of improvement isreduced time spent gathering data with fewer errors(B), showing that AI has streamlined data extraction, consolidation, and initial validation without compromising quality. AAIA's content on AI in audit processes highlights benefits such asautomation of repetitive tasks, improved coverage, and higher-quality evidence.
Extended timelines for retraining (A) suggest inefficiency rather than improvement. Eliminating human judgment (C) is neither realistic nor recommended; professional skepticism and auditor judgment remain essential. Relying on unstructured data with minimal cleansing (D) can increase risk of misinterpretation or noise. Therefore, more efficient and accurateevidence compilationis the clearest positive outcome.
References:
ISACA,AAIA Exam Content Outline- Domain 3: AI Auditing Tools and Techniques (efficiency and quality improvements in audit).
ISACA internal audit and data analytics guidance on AI's value in evidence collection.
NEW QUESTION # 216
The PRIMARY objective of auditing AI systems is to:
Answer: C
Explanation:
The AAIATM Study Guide outlines the primary goal of auditing AI systems as ensuring that they operate ethically, transparently, and fairly. This includes identifying potential biases in decision- making and confirming that the rationale behind outcomes can be explained and understood.
"The key focus of an AI audit is to evaluate whether the system performs within the parameters of fairness, legality, and accountability. This involves testing for bias and ensuring decision-making transparency."
NEW QUESTION # 217
Which of the following components would MOST effectively address cumulative benefits as part of reinforcement learning (RL)?
Answer: A
Explanation:
In Reinforcement Learning, the goal is to maximize long-term rewards. While the " Reward Function " provides immediate feedback for an action, the " Value Function " estimates the " cumulative benefit " or the total expected reward an agent can gain from a particular state moving forward. For an auditor, understanding the value function is crucial because it governs the agent ' s long-term strategy and decision-making logic. If the value function is poorly defined, the AI might take actions that yield immediate points but lead to long- term failure or unethical shortcuts.
NEW QUESTION # 218
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