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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Audit |
| Exam Number: | AAIA |
| Available Languages: | English |
| Exam Format: | Computer-Based, Multiple Choice, Remotely Proctored |
| Passing Score: | 65% |
| Real Exam Qty: | 90 |
| Exam Duration: | 120 minutes |
| Related Certifications: | CIA CPA FCCA CISA ACCA |
| Sample Questions: | ISACA AAIA Sample Questions |
| Exam Way: | Online remotely proctored computer-based exam |
| Pre Condition: | Candidates must hold an active CISA certification or another qualified audit-related designation such as CIA, CPA, ACCA, FCCA, Canadian CPA, Australian CPA/FCPA, or Japanese CPA. |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aaia |
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NEW QUESTION # 45
Which of the following BEST helps in detecting AI model drift?
Answer: B
Explanation:
Detecting model drift requires a point of comparison and real-time visibility. The AAIA™ manual identifies the best practice as " Establishing a performance baseline " (using metrics like accuracy or F1-score from the initial validation phase) and then " Implementing continuous monitoring " to track those metrics as the model processes live production data. Any significant deviation from the baseline serves as an early warning that the model ' s environment has shifted and retraining is necessary. Periodic reviews (Option A) are helpful but may not detect drift quickly enough to prevent erroneous decisions in dynamic environments.
NEW QUESTION # 46
Which regulatory framework introduces a risk-tiered classification (unacceptable, high, limited, minimal) for AI systems?
Answer: D
Explanation:
The EU AI Act classifies AI systems into risk tiers, with high-risk systems subject to conformity assessments, documentation, and human oversight requirements.
NEW QUESTION # 47
Which of the following is MOST important to consider when auditing an organization's AI procedures?
Answer: C
Explanation:
The integrity of data fed into AI systems is a critical concern. The AAIA™ Study Guide emphasizes that validation and filtration processes are essential to mitigate the risk of data poisoning-an attack that can manipulate model behavior by injecting malicious inputs.
"Data poisoning represents a major vulnerability in AI pipelines. Effective controls include robust validation, filtration, and monitoring of training data sources. These preventive practices are essential to ensure model reliability and security." While options A, B, and C are important operational and training measures, only D addresses a technical risk that can directly compromise model outputs and trustworthiness.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "AI Data Integrity and Attack Prevention"
NEW QUESTION # 48
An organization's fraud detection model achieves high accuracy on its initial data set but performs poorly in production. After a complex neural network was trained, the training accuracy was significantly higher than the validation accuracy. Which of the following is the MOST likely cause?
Answer: D
Explanation:
"Overfitting" occurs when a complex model, such as a deep neural network, learns the "noise" and specific details of the training data rather than the general underlying patterns. A clear indicator of overfitting is a large gap between training performance and validation/test performance. According to the AAIATM manual, this makes the model brittle and unable to generalize to new, unseen data in a production environment. To mitigate this, auditors should recommend techniques such as regularization, dropout, or simplifying the model architecture.
NEW QUESTION # 49
An IS auditor detected a " Prompt Injection " embedded in an email from a vendor that used an invisible font to hide text. Which of the following is the BEST control?
Answer: A
Explanation:
This is a " Hidden Text " attack, where an attacker tricks an LLM by embedding instructions that the human reader cannot see but the machine can process. The most effective " Incident Management " control is " Text Sanitization " that specifically strips out invisible formatting, hidden HTML tags, or zero-width characters before the text is sent to the AI. Adding instructions (Option B) is unreliable because prompt injections are specifically designed to " override " previous instructions. Lowering the temperature (Option A) reduces creativity but doesn ' t stop the model from following a clear, albeit hidden, command.
NEW QUESTION # 50
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