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ISACA AAIA Exam Overview:

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

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	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	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 (Q114-Q119):

NEW QUESTION # 114
Which of the following is the BEST evidence that an organization performs ongoing bias monitoring (versus only a one-time pre-deployment assessment)?

A. A signed ethics policy
B. A single fairness report from the initial model validation
C. An initial data quality assessment
D. Recurring, scheduled fairness metric reporting integrated into the production monitoring dashboard

Answer: D

Explanation:
Bias can emerge or worsen over time as data and usage patterns shift; only continuous, scheduled monitoring -- not a one-time check -- provides assurance that fairness is maintained post-deployment.

NEW QUESTION # 115
An IS auditor is looking to expedite reporting for an audit with complex issues. Which of the following would be the MOST effective way for the auditor to use generative AI?

A. Developing action items discussed in closing meetings for management action plans
B. Revising audit conclusions with precise verbiage to describe the audit observations
C. Developing a draft of an executive summary based on detailed findings and audit scope
D. Revising audit background and scope information based on new information from management

Answer: C

NEW QUESTION # 116
Which of the following is the BEST way to mitigate data poisoning in an AI model?

A. Increase training data set size.
B. Implement robust data validation protocols.
C. Rely on external third-party model providers.
D. Use simpler algorithms to improve explainability.

Answer: B

Explanation:
Data poisoningoccurs when attackers manipulate training data to corrupt model behavior. The most direct mitigation is to implementrobust data validation and integrity checks(option C), including anomaly detection on input distributions, provenance controls, verification of data sources, and safeguards for pipelines feeding the training set. AAIA highlightsthreats and vulnerabilities specific to AIand the importance of controls that protect data integrity in AI Operations.
Option A (relying on third-party providers) does not inherently eliminate poisoning risk; providers themselves may be vulnerable. Option B (increasing data size) can dilute but not reliably remove malicious samples.
Option D (simpler algorithms) might help interpretability but does not directly prevent poisoned data from influencing the model. The most effective, aligned control isrigorous data validationto ensure only trustworthy data enters the training process.
References:
ISACA,AAIA Exam Content Outline- Domain 2: Threats and Vulnerabilities Specific to AI (controls for AI- related threats).
ISACA risk guidance referencing data integrity and poisoning risks in AI pipelines.

NEW QUESTION # 117
Which of the following is the BEST way to test for proxy discrimination in a model that does not directly use a protected attribute (e.g., race)?

A. Increase the model's regularization parameter
B. Reduce the number of training epochs
C. Remove all numeric features
D. Test whether other correlated features (e.g., zip code) act as proxies that reproduce the same disparate outcomes

Answer: D

Explanation:
Proxy discrimination occurs when non-protected features correlate strongly with a protected attribute, effectively reintroducing bias. Correlation and outcome analysis on such features helps detect this.

NEW QUESTION # 118
What should be done FIRST when an AI-powered chatbot starts giving incorrect financial advice after a backend API change?

A. Push a patch to improve chatbot response speed.
B. Add more rules to override the model's output.
C. Retrain the model with historical and updated data.
D. Suspend the chatbot and assess the impact.

Answer: D

Explanation:
When an AI system begins givingincorrect financial advice, the FIRST step is tosuspend the chatbot(D) to prevent ongoing harm. AAIA emphasizes protecting users from unsafe decisions as the top priority in AI operations.
Suspension allows the organization to:
* Stop distribution of harmful advice
* Assess impact and identify faulty API dependencies
* Prevent regulatory or customer harm
* Conduct root-cause analysis safely
Retraining (C) is corrective but must occurafterassessment. Adding rules (B) risks masking deeper issues.
Speed patches (A) are irrelevant to correctness.
References:
AAIA Domain 2: Incident Management, Safety Controls, and Output Validation

NEW QUESTION # 119
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