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ISACA AAIA Exam Overview:

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

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	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 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 (Q170-Q175):

NEW QUESTION # 170
An IS auditor notes that an AI model achieved significantly better results on training data than on test dat a. Which of the following problems with the model has the IS auditor identified?

A. Bias
B. Generalization
C. Underfitting
D. Overfitting

Answer: D

NEW QUESTION # 171
To confirm the fairness of AI model decisions, the BEST way to collect reliable evidence during an AI audit is by:

A. Interviewing developers.
B. Testing the model with a curated sample data set.
C. Observing the system's interactions with end users.
D. Analyzing system metadata.

Answer: B

NEW QUESTION # 172
Which of the following would provide the BEST evidence to an IS auditor that an AI model's outputs are effectively controlled for bias?

A. Model training is restricted to data containing real-world human decisions.
B. Accuracy ranges for various demographic groups are similar.
C. The organization's AI policies include a clear definition of fairness.
D. Technical details of model development processes are transparent.

Answer: B

Explanation:
To determine whether an AI model's outputs are effectively controlled for bias, an auditor needs empirical performance evidence across demographic groups. Similar accuracy ranges across groups (A) demonstrate that the model performs equitably and does not disproportionately advantage or disadvantage specific populations. This aligns with AAIA's emphasis on fairness metrics, such as disparate error rates, equal opportunity, and demographic parity analyses.

NEW QUESTION # 173
Which of the following BEST describes the auditor's role when reviewing an organization's AI governance maturity?

A. Independently assessing whether governance structures, policies, and controls are designed and operating effectively across the AI lifecycle
B. Managing the organization's data science team
C. Approving all new AI projects before development begins
D. Building the AI models being audited

Answer: A

Explanation:
The auditor's role is independent assurance -- evaluating whether governance, risk, and control structures exist and function effectively -- not operational involvement in building or approving AI systems.

NEW QUESTION # 174
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?

A. The cloud provider has not adopted an ethical AI governance framework
B. Cloud provider employees have limited AI skills
C. AI model audit trails have not been comprehensively documented
D. The service level agreement (SLA) does not include network latency and inference guarantees

Answer: D

Explanation:
In areal-time predictionenvironment (e.g., fraud detection, medical triage, automotive risk),latency and inference speeddirectly affect safety, accuracy, and business performance.
If the SLAdoes 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
Although audit trails (B) and governance frameworks (D) are important, theoperational riskrelated to latency is the most immediate and severe.
Limited AI skills among cloud employees (A) is not directly relevant since customers maintain operational responsibility.
References:
AAIA Domain 2: AI Operations - Real-Time Systems, Performance Guarantees

NEW QUESTION # 175
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