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ISACA AAIA Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Audit (AAIA) Exam
Exam Number:	AAIA
Exam Format:	Computer-based, Remote proctoring or test center, Multiple-choice, Closed-book
Related Certifications:	CISA CIA CPA
Certificate Validity Period:	Not publicly specified (requires ongoing CPE maintenance after certification)
Passing Score:	65%
Available Languages:	English
Exam Duration:	120 minutes
Exam Price:	USD 459 (member), USD 599 (non-member)
Real Exam Qty:	55
Recommended Training:	ISACA AI Audit Training Resources Official AAIA Training Course Providers
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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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.

ISACA Advanced in AI Audit Sample Questions (Q256-Q261):

NEW QUESTION # 256
When auditing a research agency's use of generative AI models for analyzing scientific data, which of the following is MOST critical to evaluate in order to prevent hallucinatory results and ensure the accuracy of outputs?

A. The frequency of data audits verifying the integrity and accuracy of inputs
B. The measures in place to ensure the appropriateness and relevance of input data for generative AI models
C. The effectiveness of data anonymization processes that help preserve data quality
D. The algorithms for generative AI models designed to detect and correct data bias before processing

Answer: B

Explanation:
Ensuring that input data is appropriate and relevant (option D) is the most critical factor in preventing hallucinations--where generative models produce fabricated or misleading outputs.
The AAIATM Study Guide notes, "Generative models are highly sensitive to input data; inaccurate, irrelevant, or inappropriate inputs increase the likelihood of nonsensical or incorrect outputs." While bias detection, data quality audits, and anonymization are important, ensuring the relevance and suitability of input data is foundational for reliable generative AI performance.

NEW QUESTION # 257
Which of the following is the MOST important course of action for an organization prior to allowing end users to utilize an AI tool?

A. Develop an AI policy with guidelines on appropriate use.
B. Determine the impact to the disaster recovery plan (DRP).
C. Implement baseline performance metrics.
D. Ensure a cybersecurity insurance clause is in place to include the use of AI.

Answer: A

Explanation:
An AI usage policy sets the foundation for safe, ethical, and effective AI deployment. According to the AAIA™ Study Guide, having an AI policy in place ensures that users understand acceptable behaviors, limitations, and responsibilities when interacting with AI tools.
"AI acceptable use policies promote governance by clearly outlining the dos and don'ts of AI interaction, preventing misuse and aligning user activity with organizational values and compliance standards." Other actions (B, C, D) are important in operations and risk management but should follow the establishment of governance protocols through a usage policy. Hence, A is the highest-priority prerequisite.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Policy Frameworks for End-User AI Interaction"

NEW QUESTION # 258
Which of the following is the MOST significant benefit of performing frequent AI model testing and retraining?

A. Removing unnecessary model features
B. Ensuring model scalability
C. Ensuring the model is updated with current data
D. Assessing the impact of attacks

Answer: C

Explanation:
AI models are not " static " systems; they are reflections of the data they were trained on. In dynamic environments, data patterns change constantly (e.g., market trends or new fraud tactics). Frequent testing and retraining ensure the model is " updated with current data, " which prevents performance degradation and " data drift. " While testing can assess attacks (Option A), the primary operational reason for a recurring retraining schedule is to maintain the model ' s relevance and accuracy against the most recent real-world behaviors.

NEW QUESTION # 259
Which of the following is the MOST frequent cause of generative AI model hallucinations?

A. Outdated model cards
B. Weak access controls
C. Inadequate data quality
D. Inconsistent change management

Answer: C

Explanation:
Hallucinations-instances where a generative model produces factual errors or nonsensical information with high confidence-are primarily caused by " Inadequate data quality " in the training set. If the model is trained on data that is contradictory, incomplete, or contains " noise " (incorrect facts), it fails to learn accurate semantic relationships. The ISACA AAIA™ manual highlights that " Data Cleaning " and " Provenance " are essential to mitigate this. While weak controls (Option C) or poor change management (Option D) can lead to other risks, the mathematical root of the hallucination itself is typically found in the underlying quality and accuracy of the training data.

NEW QUESTION # 260
A bank uses a video-based know your customer (KYC) verification process. Cybercriminals exploit this process by using deepfake technology to impersonate bank customers. Which of the following countermeasures is the BEST way for the bank to mitigate this risk?

A. Encrypting all customer data and communication
B. Requesting additional identity and address documents for verification
C. Discontinuing the use of the video-based verification process
D. Leveraging AI-based liveness detection during video verification

Answer: D

NEW QUESTION # 261
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