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ISACA AAIA Exam Overview:

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

TopicDetails
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 (Q290-Q295):

NEW QUESTION # 290
Which of the following should be an IS auditor's GREATEST concern when using a predictive AI tool to analyze data abnormalities?

Answer: C

Explanation:
For apredictive AI tool analyzing abnormalities, the GREATEST concern is therate and impact of false positives and false negatives(A). False positives can lead to unnecessary investigation, while false negatives mean true issues (e.g., fraud, control failures) remain undetected. From an assurance perspective, false negatives are especially critical because they directly undermine audit objectives. AAIA underscores that key performance metrics (e.g., precision, recall) and error trade-offs are essential in evaluating AI tools used in audit.
Integration ease (B), speed (C), and cost (D) are important practical considerations but are secondary to whether the toolaccurately identifies or misses significant anomalies. Therefore, error behavior-false positives and false negatives-represents the primary risk to audit quality.
References:
ISACA,AAIA Exam Content Outline- Domain 3: AI in Audit Processes; Domain 2: AI Operations (model performance metrics and risk).
ISACA analytics guidance on evaluating AI tools using precision, recall, and error analysis in audit contexts.


NEW QUESTION # 291
An organization uses an AI image generation platform to create promotional materials. An IS auditor identifies that the platform includes copyrighted images in its training data. Which of the following is the auditor's BEST recommendation to address this issue?

Answer: B

Explanation:
Ensuring that AI tools are trained on properly licensed and documented data sets is critical to avoiding copyright infringement and legal exposure. The AAIA™ Study Guide emphasizes using platforms with certified and traceable training data to meet ethical and legal standards.
"Organizations must verify the provenance and licensing of data used to train AI systems. Platforms that certify data sources reduce the risk of using protected intellectual property without consent." Manual review (A) is resource-intensive and may not detect embedded copyright violations. Labeling (C) is not sufficient for legal protection. Suspension (D) may be excessive without first attempting remediation.
Thus, B is the most strategic and effective recommendation.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Intellectual Property and Data Licensing in AI Systems"


NEW QUESTION # 292
Which control is MOST important to verify in order to ensure proper data management with AI systems?

Answer: D

Explanation:
According to the ISACA AAIATM Study Guide, a "Data Governance Framework" is the foundational control. It provides the policies, roles (stewards, owners), and standards necessary to manage the entire data lifecycle. Without a framework, activities like inventorying (Option C) or labeling (Option D) are ad-hoc and lack accountability. A formal framework ensures that data management is consistent, compliant with privacy laws, and aligned with the organization's risk tolerance. It is the "enabling" control that makes all other data quality and security metrics meaningful and enforceable.


NEW QUESTION # 293
An organization uses an AI image generation platform to create promotional materials. An IS auditor identifies that the platform includes copyrighted images in its training dat a. Which of the following is the auditor's BEST recommendation to address this issue?

Answer: B


NEW QUESTION # 294
What is the PRIMARY reason to establish a "kill switch" or manual override capability for an autonomous AI system?

Answer: A

Explanation:
A kill switch provides a critical safety control, allowing operators to immediately halt an AI system exhibiting harmful, erratic, or non-compliant behavior before further damage occurs.


NEW QUESTION # 295
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