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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Audit (AAIA) Exam |
| Exam Number: | AAIA |
| Exam Duration: | 120 minutes |
| Exam Price: | USD 459 (member), USD 599 (non-member) |
| Real Exam Qty: | 55 |
| Exam Format: | Computer-based, Closed-book, Multiple-choice, Remote proctoring or test center |
| Available Languages: | English |
| Certificate Validity Period: | Not publicly specified (requires ongoing CPE maintenance after certification) |
| Passing Score: | 65% |
| Related Certifications: | CISA CPA CIA |
| Recommended Training: | Official AAIA Training Course Providers ISACA AI Audit Training Resources |
| Exam Registration: | ISACA AAIA Certification Page |
| Sample Questions: | ISACA AAIA Sample Questions |
| Exam Way: | Computer-based exam delivered via PSI test centers or remote proctoring |
| Pre Condition: | Must hold an active CISA, CIA, CPA, or equivalent ISACA-approved advanced auditing certification |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aaia |
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NEW QUESTION # 48
Which of the following is the MOST important consideration for change management related to the organization-wide adoption of AI systems and tools?
Answer: B
Explanation:
For organization-wide adoption of AI, the MOST important change management consideration is that the organization has suitable data governance and infrastructure readiness (D). Without robust data governance, AI systems may rely on poor-quality, noncompliant, or insecure data; without appropriate infrastructure (compute, storage, monitoring, integration), implementations will be fragile, unreliable, and risky. AAIA stresses that AI readiness includes governance structures, data stewardship, and technical foundations.
NEW QUESTION # 49
An IS auditor observes that an AI-based fraud detection system used by an insurance organization produces inconsistent outcomes when processing similar cases. Which of the following is the auditor's MOST efficient recommendation?
Answer: A
Explanation:
Inconsistent outcomes for similar cases often indicate issues with "Model Stability" or "Data Quality". The most efficient recommendation is to "Analyze the training data and model evaluation parameters" to identify if the model was trained on biased, noisy, or non-representative datasets.
Inconsistencies may also stem from poorly tuned hyperparameters that cause the model to react erratically to minor variations in input.
NEW QUESTION # 50
Which of the following is the GREATEST risk associated with deploying an AI system with ineffective anomaly detection?
Answer: B
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 # 51
An AI tool is being implemented for a regional healthcare organization. Which of the following training methods BEST ensures the AI output does not reveal whether someone's personal data was used?
Answer: C
Explanation:
Differential privacyintroduces carefully calibrated noise during training or query responses so that it becomes mathematically difficult to infer whether any specific individual's record is included in the training set. For healthcare data-highly sensitive and subject to strict privacy laws-this technique directly supports privacy-by-design, reducing the risk that model outputs leak membership information or reconstruct personal records.
Option A uses real patient records directly and does not, by itself, mitigate inference risk. Option B (data augmentation) may expand the dataset but does not guarantee resistance to membership inference attacks.
Option D (transfer learning using public data) can help, but if any private data is used in fine-tuning, privacy risks remain. Differential privacy, as in option C, is the most appropriate control to ensure that outputs do not reveal whether particular personal data was used.
References:
ISACA,AAIA Exam Content Outline- Domain 1: Privacy and Data Governance Programs; Domain 2: Data Management Specific to AI (data confidentiality, data security).
ISACA guidance on privacy-by-design and AI risk management concepts reflected in AAIA.
NEW QUESTION # 52
When reviewing contracts or other lengthy documentation in the planning phase, which of the following tools would BEST extract relevant information?
Answer: C
Explanation:
Natural Language Processing (NLP) enables systems to understand, summarize, and extract relevant insights from unstructured text data such as contracts, emails, or reports. The AAIATM Study Guide recognizes NLP as the optimal tool for document review during audit planning or risk assessment phases.
"NLP techniques can efficiently process large volumes of documentation, highlight key clauses, and identify inconsistencies or risk indicators. This enhances audit productivity and thoroughness."
NEW QUESTION # 53
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