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ISACA AAIA Exam Syllabus Topics:

Topic
Details

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

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 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 (Q161-Q166):

NEW QUESTION # 161
Which of the following is the GREATEST risk associated with using AI in audit planning?

A. Incomplete data
B. Scope creep
C. Limited knowledge
D. Increased planning costs

Answer: A

NEW QUESTION # 162
An IS auditor is evaluating an organization's data governance controls for its AI system. Which of the following represents the GREATEST risk in this context?

A. Lack of procedures for automated data backup
B. Inadequate controls over data accuracy and privacy compliance
C. Inconsistent data management practices
D. Limited frequency of AI system performance and data accuracy reviews

Answer: B

Explanation:
In AI systems,data accuracy and privacyare foundational to both performance and regulatory compliance.
Inadequate controls over data accuracy and privacy compliance(D) pose thegreatest risk, as they can lead to incorrect decisions, legal violations, regulatory penalties, and significant reputational damage. AAIA emphasizes that data governance programs must ensure data is accurate, secure, lawfully processed, and appropriately protected throughout the AI life cycle.
Option A (inconsistent practices) is concerning but is often a symptom of underlying governance weaknesses; its impact is most severe when it affects accuracy and privacy. Option B focuses on backup procedures, which are important for availability and resilience, but not as central to AI decision quality and legal risk. Option C (limited performance and accuracy reviews) is serious but again narrower than outright inadequacy of key controls over accuracy and privacy.
References:
ISACA,AAIA Exam Content Outline- Domain 1: Privacy and Data Governance Programs (accuracy, privacy, and governance controls).
ISACA data governance and privacy guidance for AI systems.

NEW QUESTION # 163
The PRIMARY objective of auditing AI systems is to:

A. Optimize user experience and interface satisfaction.
B. Maximize system efficiency and throughput.
C. Identify biases and decision transparency.
D. Minimize algorithm latency and information storage impacts.

Answer: C

Explanation:
The AAIA™ Study Guide outlines the primary goal of auditing AI systems as ensuring that they operate ethically, transparently, and fairly. This includes identifying potential biases in decision-making and confirming that the rationale behind outcomes can be explained and understood.
"The key focus of an AI audit is to evaluate whether the system performs within the parameters of fairness, legality, and accountability. This involves testing for bias and ensuring decision-making transparency." Options B, C, and D refer to performance and usability concerns, which are secondary to the ethical and governance-focused purpose of AI audits.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "Purpose and Scope of AI Audits"

NEW QUESTION # 164
Which of the following do supervised AI learning models PRIMARILY use to train algorithms?

A. Labeled data sets
B. Unlabeled data sets
C. Randomized data sets
D. Clustered data sets

Answer: A

NEW QUESTION # 165
Which of the following should be applied to an AI system but are not typically used in traditional systems?

A. Controls to manage data governance
B. Controls to prevent data exfiltration
C. Controls to monitor data poisoning
D. Controls to protect data privacy

Answer: C

Explanation:
AI systems faceunique threatsnot commonly found in traditional IT environments, particularlydata poisoning, where attackers manipulate training data to corrupt model behavior. Controls that specifically monitor and mitigate poisoning-such as input provenance checks, anomaly detection on training data, and integrity validation pipelines-are emphasized in AAIA's coverage ofAI-specific vulnerabilities.
While privacy (A), data exfiltration (C), and data governance (D) controls are essential for all digital systems, monitoring for data poisoningis uniquely critical for AI because poisoned inputs can lead to faulty predictions, safety issues, or systemic bias. AAIA specifically highlights data poisoning as a distinct threat requiring specialized controls.
References:
ISACA,AAIA Exam Content Outline- Domain 2: Threats and Vulnerabilities Specific to AI.
ISACA AI security guidance discussing poisoning and integrity attacks.

NEW QUESTION # 166
......

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Will White Will White

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