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ISACA AAIA Exam Overview:

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

Topic	Details
Topic 1	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 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	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.

ISACA Advanced in AI Audit Sample Questions (Q161-Q166):

NEW QUESTION # 161
Which of the following is the PRIMARY benefit of using linear regression in machine learning (ML) when transparency and auditability are required?

A. Reduction of model bias
B. Predictive accuracy
C. Avoidance of overfitting
D. Ease of interpretation

Answer: D

Explanation:
Linear regression is a " transparent " or " white-box " model. Its primary benefit in an audit context is its interpretability; each coefficient directly indicates the influence of an input variable on the output. This allows auditors to easily verify the logic and ensure that no inappropriate or discriminatory variables are driving the results. While linear models are less prone to complex overfitting than deep learning, they are not immune to it. Their simplicity often results in lower predictive accuracy for complex data, but for auditability and compliance, the ability to explain the " why " behind a prediction is paramount.

NEW QUESTION # 162
A bank is deploying an AI model trained on customer transactions in a multi-cloud environment.
Which of the following BEST supports regulatory compliance regarding data security and privacy?

A. Privacy by design
B. Data residency and sovereignty controls
C. Data governance framework
D. Data protection impact assessment (DPIA)

Answer: B

Explanation:
In a multi-cloud environment, data often traverses various geographical regions. For financial institutions, "Data residency and sovereignty" are the most critical compliance factors, ensuring that data is stored and processed within the jurisdictions required by law (e.g., GDPR or local banking acts). Failure to control where data resides can lead to severe legal penalties. While
"Privacy by Design" and "DPIA" are essential methodologies, they do not specifically address the physical and legal location of data across cloud providers. Sovereignty controls ensure the bank maintains control over its data assets and complies with specific cross-border data transfer regulations.

NEW QUESTION # 163
In order to streamline operations, a bank has deployed an AI application to automatically detect and prevent further fraud on accounts. However, customers have voiced concerns that their usual transactions are being rejected. Which of the following is the MOST likely cause of the false positives?

A. The hyperparameters are not optimized.
B. Consent is not properly managed.
C. Data versioning controls were not developed.
D. Compute scale training was not performed.

Answer: A

NEW QUESTION # 164
An IS auditor is reviewing an AI application that uses customer data to refine the organization's marketing outreach strategies. Which of the following should be the auditor's PRIMARY focus during this review?

A. Compliance with applicable privacy regulations
B. Escalation protocols for sensitive data breaches
C. Alignment with organizational AI strategies
D. Access control design and effectiveness

Answer: A

Explanation:
Since the AI system processes customer data--including potentially personal, sensitive, or behavioral data--the auditor's primary focus must be privacy compliance (C). AAIA identifies privacy violations as one of the highest-risk areas for organizations using AI.
The auditor must ensure:
Data collection follows lawful basis requirements
Customers gave proper consent (if required)
Processing adheres to data minimization and purpose limitation
Storage and retention policies meet regulatory standards
Data subjects' rights (access, correction, deletion) are protected
Third-party or cross-border transfers are compliant

NEW QUESTION # 165
Which of the following is the PRIMARY objective of AI governance?

A. Implementing compliance and ethics controls for AI initiatives
B. Promoting a positive return on investment (ROI) from AI projects
C. Defining clear roles and responsibilities for AI development, use, and oversight
D. Ensuring controls over AI are designed well and operate effectively

Answer: C

NEW QUESTION # 166
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