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ISACA AAIA Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Audit
Exam Number:	AAIA
Real Exam Qty:	90
Available Languages:	English
Exam Duration:	120 minutes
Exam Format:	Computer-Based, Multiple Choice, Remotely Proctored
Passing Score:	65%
Related Certifications:	CPA CISA CIA FCCA ACCA
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 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	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 (Q327-Q332):

NEW QUESTION # 327
Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

A. Using customer service metrics for service speed and food quality to predict customer retention and forecast revenue
B. Basing driver retention and termination decisions on the number of delivered orders per total hours worked as compared to an industry benchmark
C. Comparing total food preparation and delivery time to an industry benchmark to set key performance and risk indicators for individual restaurants
D. Correlating time, cost, delivery distance, and customer satisfaction metrics to issue coupons to customers receiving substandard service

Answer: B

Explanation:
Using AI to make employment decisions such as driver termination or retention introduces significant ethical risks. If based solely on performance metrics without context or human review, such systems can lead to unfair treatment or discrimination--violating principles of transparency and due process.
"Automating workforce decisions must be approached cautiously to prevent discriminatory outcomes. Ethical AI governance requires oversight when AI is used for employment-impacting decisions."

NEW QUESTION # 328
Which of the following is the PRIMARY objective of AI governance?

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

Answer: D

Explanation:
The AAIATM Study Guide defines the primary objective of AI governance as establishing structure and accountability for AI initiatives. This includes clearly assigning responsibilities across development, deployment, risk management, and auditing roles to ensure that AI is used responsibly and transparently.
"AI governance establishes the policies, roles, and oversight structures that guide the ethical and secure deployment of AI. Clear accountability helps prevent unauthorized use and ensures strategic alignment."

NEW QUESTION # 329
An IS auditor is planning an audit covering a vendor-provided and supported AI model used by the organization to predict train track maintenance. Which of the following is the BEST approach for the IS auditor to test the model?

A. Extensive code reviews
B. Gray box testing
C. Black box testing
D. White box testing

Answer: C

Explanation:
When auditing vendor-provided (third-party) AI models, the organization often lacks access to the underlying source code, neural network architecture, or weights. In such cases, the AAIATM manual recommends "Black Box Testing" as the most practical and effective approach. This involves testing the model based solely on its inputs and outputs to verify its predictive accuracy, fairness, and reliability without needing internal technical details.

NEW QUESTION # 330
While evaluating a complex machine learning (ML) model used for regulatory compliance in a financial institution, which of the following should the IS auditor do to BEST ensure transparency?

A. Document sources and data processes.
B. Create dashboards to show outputs.
C. Provide periodic model audit reports.
D. Use tools that explain model decisions.

Answer: D

Explanation:
Transparency in AI, especially in regulated sectors like finance, is best achieved by using explainability tools that interpret the internal workings and outputs of complex ML models. The AAIATM Study Guide highlights model explainability as essential for both auditors and regulators to understand why certain decisions are made.
"Explainability tools allow auditors to trace predictions back to input features, helping verify fairness, logic, and compliance. These tools support transparency and trustworthiness in black- box models."

NEW QUESTION # 331
Which of the following AI solutions is BEST used to generate standardized reports using unstructured customer feedback?

A. Predictive analytics
B. Recommendation engines
C. Natural language processing (NLP)
D. Anomaly detection

Answer: C

Explanation:
Natural Language Processing (NLP) is the branch of AI specifically designed to handle unstructured text. In an audit or business context, NLP tools can perform "sentiment analysis" and "entity extraction" on large volumes of customer feedback to identify common themes, complaints, or positive trends. According to ISACA, NLP is the optimal choice for converting qualitative, human-written text into structured, standardized reports that auditors can use for objective analysis.

NEW QUESTION # 332
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