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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit
Exam Number:AAIA
Related Certifications:FCCA
CISA
CPA
CIA
ACCA
Available Languages:English
Exam Duration:120 minutes
Real Exam Qty:90
Exam Format:Computer-Based, Remotely Proctored, Multiple Choice
Passing Score:65%
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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ISACA AAIA Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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.

ISACA Advanced in AI Audit Sample Questions (Q56-Q61):

NEW QUESTION # 56
An IS auditor is reviewing AI-driven processes that automate financial approvals. Which of the following poses the GREATEST challenge to maintaining separation of duties (SOD)?

Answer: B

Explanation:
Separation of Duties (SOD) is intended to prevent errors or fraud by ensuring no single person (or entity) has control over all stages of a transaction. When AI automates financial approvals, the
"Lack of transparency in the algorithm" creates a challenge because the logic that grants approval is often opaque. If the algorithm functions as a "Black Box," it may consolidate decision- making power that was previously spread across multiple human roles, without sufficient visibility into how those decisions are made. This can lead to unauthorized or erroneous approvals going undetected. Effective AI governance must ensure that automated approvals are subject to transparent audit trails and secondary human reviews to uphold SOD principles.


NEW QUESTION # 57
Which of the following techniques would be MOST effective as part of incident management procedures for a prompt injection attack?

Answer: A

Explanation:
Prompt injection attacks involve maliciously crafted inputs intended to override system instructions, exfiltrate data, or cause harmful behavior. The most effective control aligned with incident management is to deploy robust input validation and sanitization (C), which includes rules and filters designed to detect and neutralize potentially malicious content before it reaches the model. AAIA's coverage of AI threats and vulnerabilities highlights the importance of input validation and secure prompt handling for generative AI systems.


NEW QUESTION # 58
The PRIMARY purpose of maintaining an audit trail in AI systems is to:

Answer: D

Explanation:
Audit trails in AI systems serve to document the inputs, processes, and outputs of AI decisions, allowing stakeholders and auditors to trace how decisions were made. The AAIATM Study Guide identifies transparency and traceability as the core functions of an AI audit trail.
"Maintaining audit logs is critical to explainability and accountability. It ensures that decisions made by AI systems can be reconstructed and assessed for accuracy, ethics, and legality."


NEW QUESTION # 59
Which of the following is MOST important for an IS auditor to consider when identifying AI risk in a know your customer (KYC) application within a banking organization?

Answer: A

Explanation:
In high-stakes financial applications like KYC, the primary concern is the potential business and regulatory impact of an AI error--such as false customer rejection or failure to detect fraudulent accounts. The AAIATM Study Guide emphasizes aligning AI risk assessments with business impact and regulatory exposure.
"In financial institutions, the most material risk of AI errors lies in operational disruption and regulatory fines. KYC models must be assessed for how errors can lead to compliance failures or reputational harm."


NEW QUESTION # 60
When converting data categories before training an AI model, which of the following scenarios represents the GREATEST risk?

Answer: D

Explanation:
The AAIA™ Study Guide emphasizes that encoding categorical variables must preserve the semantic meaning and order of categories when relevant. The greatest risk occurs when ordinal data-such as customer rewards tiers-is treated as nominal through one-hot encoding, which removes the inherent order and may impair model learning.
"Improper encoding of ordinal variables as nominal can distort the model's understanding of relationships, leading to inaccurate predictions or biased outcomes." Customer reward categories (economy < business < first class) have a natural order. One-hot encoding ignores this order, potentially degrading model accuracy. Other options represent nominal data and are appropriately encoded.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Fundamentals and Technologies," Subsection: "Data Preprocessing and Feature Engineering"


NEW QUESTION # 61
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