ISACA AAIA Practice Online, AAIA New Study Questions

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ISACA AAIA Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Audit
Exam Number:	AAIA
Passing Score:	65%
Related Certifications:	ACCA CIA CISA FCCA CPA
Exam Duration:	120 minutes
Exam Format:	Remotely Proctored, Computer-Based, Multiple Choice
Available Languages:	English
Real Exam Qty:	90
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	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	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 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 (Q172-Q177):

NEW QUESTION # 172
Which regulatory framework introduces a risk-tiered classification (unacceptable, high, limited, minimal) for AI systems?

A. SOX
B. EU AI Act
C. PCI DSS
D. GDPR

Answer: B

Explanation:
The EU AI Act classifies AI systems into risk tiers, with high-risk systems subject to conformity assessments, documentation, and human oversight requirements.

NEW QUESTION # 173
When an IS auditor uses generative AI with external RAG (retrieval-augmented generation) to gather evidence during an audit, which of the following poses the GREATEST data security risk?

A. The model might fail to retrieve data from the vector.
B. External search engines only respond to public data.
C. Personal information may be shared based on model training data.
D. Sensitive internal context may be included in queries sent to external services.

Answer: D

Explanation:
The GREATEST risk is that sensitive internal content may be embedded in AI prompts and sent to an external system (A), exposing confidential or regulated information. Retrieval-augmented generation often involves sending queries or embeddings to third-party APIs, creating a significant data leakage risk if internal context is included.

NEW QUESTION # 174
During a pre-implementation risk assessment, an AI model is determined to present a significant risk of bias and potential harm in excess of the organization's risk tolerance. Which of the following is the MOST appropriate response?

A. Revisit the risk tolerance to ensure it is appropriate.
B. Enhance the data that the model is trained on.
C. Postpone deployment until the risk can be safely managed.
D. Obtain board approval for an exception.

Answer: C

Explanation:
The AAIATM Study Guide advises that if an AI model presents a risk that exceeds the organization's predefined risk tolerance--especially in cases of ethical harm or bias--deployment should be delayed until proper safeguards are in place. This approach prevents legal exposure and preserves stakeholder trust.
"When AI risks exceed acceptable thresholds, organizations must suspend implementation until corrective action reduces the risk to within tolerance levels. Proceeding without mitigation violates sound governance principles."

NEW QUESTION # 175
An organization is evaluating change management practices for AI-based decision support models. Which of the following BEST demonstrates effective AI-focused change management?

A. Engaging an independent expert to review the model's accuracy and precision on a quarterly basis
B. Documenting model updates and retraining sessions to ensure traceability
C. Assigning a single data science team member to adjust the model in order to establish accountability
D. Deploying two separate copies of the model after each adjustment to compare results

Answer: B

Explanation:
Documenting model updates and retraining sessions to ensure traceability (option C) is the hallmark of mature, audit-ready change management in AI. The AAIATM Study Guide states,
"Traceability and documentation of all changes--including retraining events, parameter adjustments, and update rationales--enable effective audit trails, accountability, and regulatory compliance for AI systems." While reviews and comparisons are useful, only comprehensive documentation guarantees ongoing transparency and effective management.

NEW QUESTION # 176
An IS auditor identified that an AI model was optimized to approve more loans to meet growth targets, which led to a rise in defaults and expected losses. Which action will BEST address this situation?

A. Require developers to adopt a model scorecard.
B. Align model reward function with long-term risk metrics.
C. Decrease the acceptance threshold used by the model.
D. Add more recent loan application data to retrain the model.

Answer: B

Explanation:
This scenario describes a "misaligned objective," where the AI is optimizing for a short-term goal (growth) at the expense of long-term stability (risk). In AI development, particularly in Reinforcement Learning or objective-based models, the "Reward Function" defines what the model considers "success." To correct the issue, management must "Align the model reward function with long-term risk metrics," such as default rates or profitability over time. This ensures the AI makes decisions that balance growth with risk appetite.

NEW QUESTION # 177
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