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ISACA AAIA Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Audit
Exam Number:AAIA
Exam Price:US$459 (member) / US$599 (non-member)
Exam Format:Multiple-choice questions, Scenario-based questions, Computer-based testing
Certificate Validity Period:3 years
Related Certifications:FCCA
CIA
CPA
CISA
ACCA
Real Exam Qty:90
Passing Score:450 (scaled, range 200–800)
Available Languages:Spanish, Chinese, English
Exam Duration:150 minutes
Recommended Training:AAIA Review Manual
AAIA Official Review Course
Exam Registration:ISACA Official Registration
Sample Questions:ISACA AAIA Sample Questions
Exam Way:Computer-based; PSI test centers or remote proctored (remote not available in India, Mainland China, Hong Kong)
Pre Condition:Hold active CISA, CIA, CPA, ACCA, FCCA or equivalent qualified certification with IT audit/advisory focus
Official Syllabus URL:https://www.isaca.org/credentialing/aaia/aaia-exam-content-outline

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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 (Q106-Q111):

NEW QUESTION # 106
Which of the following is MOST effective in analyzing unlabeled datasets to identify anomalies?

Answer: D

Explanation:
Isolation Forest is specifically designed foranomaly detectionin unlabeled datasets. It works by isolating observations through random partitioning, making it highly effective for identifying rare, unusual, or suspicious data points without requiring labeled examples.
AAIA emphasizes using unsupervised anomaly detection techniques for scenarios involving:
* Fraud detection
* Network intrusion identification
* Operational anomaly analysisPCA (B) reduces dimensionality but is not an anomaly detector. Z-score (C) assumes normal distributions and is less effective for complex datasets. Supervised learning (D) requires labels, making it unsuitable for unlabeled anomaly detection.Isolation Forest is the most aligned with AAIA's unsupervised anomaly detection standards.
References:
AAIA Domain 1: AI Models and Learning Types.
AAIA Domain 2: Unsupervised Techniques for Anomaly Detection.


NEW QUESTION # 107
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: A

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 # 108
Which of the following should be done FIRST when developing an incident management process for AI threats?

Answer: B

Explanation:
The AAIA framework states that incident response begins with roles and responsibilities. Without clearly assigned accountability, no classification, escalation, or detection procedures can be effectively implemented.
Defining roles ensures:
Ownership of monitoring
Chain of command for incident decisions
Clear responsibility for documentation
Communication pathways
Allocation of resources for containment


NEW QUESTION # 109
An organization developed an AI model trained on its monthly data. Which of the following would be the BEST validation method to avoid data drift?

Answer: A

Explanation:
When dealing with monthly or temporal data, standard random splits (Option D) or cross-validation (Option A) can cause " temporal leakage, " where the model inadvertently learns from future data to predict the past.
According to ISACA AAIA™ principles, " Time Series " validation is the most appropriate method for sequential data. It involves training the model on a specific period (e.g., months 1-10) and testing it on the subsequent period (e.g., month 11). This approach accurately reflects how the model will perform in production and is essential for detecting data drift, as it identifies when seasonal trends or long-term shifts in customer behavior cause the model ' s accuracy to degrade over time.


NEW QUESTION # 110
Which of the following presents the GREATEST risk when an organization deploys a machine learning model in a public cloud environment for real-time predictions?

Answer: D

Explanation:
In a real-time prediction environment (e.g., fraud detection, medical triage, automotive risk), latency and inference speed directly affect safety, accuracy, and business performance.
If the SLA does not include guarantees for latency, the model may fail to deliver predictions in time, leading to:
Incorrect or delayed decisions
Transaction failures
Safety incidents in time-sensitive use cases
Compliance violations in regulated domains


NEW QUESTION # 111
......

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