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ISACA AAIA Exam Syllabus Topics:

Topic	Details
Topic 1	AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.
Topic 2	AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.
Topic 3	Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.

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ISACA Advanced in AI Audit Sample Questions (Q81-Q86):

NEW QUESTION # 81
Which of the following is the GREATEST risk when a generative AI tool used for threat detection produces inaccurate or misleading information?

A. Potential threats to organizational systems may be overlooked.
B. AI-related key risk indicator (KRI) values may become less reliable.
C. The model may exaggerate the severity of threats and vulnerabilities.
D. Prompt injection attacks may become more likely to succeed.

Answer: A

Explanation:
In the context of cybersecurity and threat detection, the "accuracy" of AI outputs is a matter of organizational safety. The greatest risk of inaccurate information (such as false negatives) is that
"Potential threats may be overlooked," leading to undetected breaches or system compromises.
This occurs when the model fails to flag a genuine anomaly as suspicious.

NEW QUESTION # 82
An IS auditor for a veterinary clinic was informed that the dog breed categorical variable is necessary for the predictive model. Which of the following introduces the MOST risk?

A. One-hot encoding was utilized.
B. Ordinal label encoding was utilized.
C. Data scaling was not utilized.
D. Clustering was not utilized.

Answer: B

Explanation:
Ordinal encoding assigns numeric values in an order (e.g., Poodle = 1, Labrador = 2, Husky = 3).
This falsely implies hierarchy or ranking among breeds, introducing bias into the model.
AAIA emphasizes that incorrect encoding of categorical variables can cause:
Artificially weighted importance
Misleading correlations
Incorrect predictions based on false order

NEW QUESTION # 83
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?

A. Data augmentation during training to improve privacy
B. Differential privacy applied during model training
C. Transfer learning using public health data sets
D. Supervised learning with labeled patient records

Answer: B

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 # 84
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?

A. Implement text sanitization that removes invisible text before ingestion.
B. Implement text sanitization that changes fonts to default.
C. Add more instructions to the AI model about ignoring invisible text.
D. Lower the temperature so the AI model is less likely to follow injections.

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 # 85
Which control BEST mitigates the risk of a machine learning model being manipulated through adversarial input perturbations?

A. Adversarial robustness testing during model validation
B. Regular password rotation
C. Role-based access control on the training pipeline
D. Data encryption at rest

Answer: A

Explanation:
Adversarial robustness testing deliberately crafts inputs designed to fool the model, allowing teams to measure and harden against evasion attacks before deployment.

NEW QUESTION # 86
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