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Quiz ISACA - Marvelous AAIA - Reliable ISACA Advanced in AI Audit Braindumps She

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Quiz ISACA - Marvelous AAIA - Reliable ISACA Advanced in AI Audit Braindumps She

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ISACA AAIA Exam Syllabus Topics:
TopicDetails
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.

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ISACA Advanced in AI Audit Sample Questions (Q20-Q25):NEW QUESTION # 20
An organization shares an AI model with external partners. One partner reports that sensitive data has been inadvertently exposed through the model's outputs. Which of the following is the IS auditor's BEST recommendation?
  • A. Retrain the model immediately and implement privacy-preserving techniques.
  • B. Disable the shared model and notify partners of the potential breach.
  • C. Audit the data pipelines of all partners to identify the source of the leak.
  • D. Limit the model's outputs to anonymized results while investigating further.
Answer: B

NEW QUESTION # 21
An organization deployed an AI-powered customer service chatbot trained using customer chat logs. During a risk assessment, which issue should be the IS auditor's GREATEST concern?
  • A. Obsolete procedures leading to inadequate data integrity validation
  • B. Limited AI model capability to incorporate new data
  • C. Reputational impacts from inaccurate chatbot responses
  • D. Insufficient access controls leading to unauthorized customer data exposure
Answer: D
Explanation:
The GREATEST concern isinsufficient access controls(D), which can lead tounauthorized exposure of customer data-a severe privacy, security, regulatory, and reputational risk. Chat logs often contain personally identifiable information and sensitive communications. AAIA prioritizesdata confidentiality, access control, and privacy obligationsas highest-risk elements, particularly for customer-interactive AI systems.
Inaccurate chatbot responses (C) affect reputation but are less severe than data breaches. Obsolete procedures (B) matter but pose less immediate harm. Limited capability to incorporate data (A) affects performance but not critical risk.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Legal and Privacy Considerations; Domain 1: AI Governance and Security Controls.

NEW QUESTION # 22
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 background and scope information based on new information from management
  • C. Developing a draft of an executive summary based on detailed findings and audit scope
  • D. Revising audit conclusions with precise verbiage to describe the audit observations
Answer: C

NEW QUESTION # 23
Which of the following is the BEST way to ensure data fed into an AI model aligns with business objectives?
  • A. Normalize the data within expected tolerances
  • B. Define new data attributes
  • C. Document the data input requirements
  • D. Change to new data sources
Answer: C
Explanation:
Documenting data input requirements (option C) ensures that all incoming data supports the business purpose, operational constraints, and intended use cases of the AI model.
AAIA highlights that aligning AI systems with business objectives starts withclear data specifications, including:
* Required fields and data formats
* Data quality thresholds
* Acceptable ranges and constraints
* Mandatory attributes
* Source system definitions
* Business rationale for each feature
Without documentation, data pipelines may ingest irrelevant, low-quality, or misaligned data, causing the model to drift away from business needs.
Normalization (A) improves preprocessing but does not ensure alignment.
Switching data sources (B) is premature without evaluating needs.
Defining new attributes (D) is secondary to documenting overall requirements.
References:
AAIA Domain 1: Business Alignment and Data Requirements
AAIA Domain 2: Input Specification Governance

NEW QUESTION # 24
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. Alignment with organizational AI strategies
  • B. Compliance with applicable privacy regulations
  • C. Escalation protocols for sensitive data breaches
  • D. Access control design and effectiveness
Answer: B
Explanation:
Since the AI system processes customer data-including potentially personal, sensitive, or behavioral data- the auditor'sprimaryfocus must beprivacy 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
Access controls (B) matter but are secondary to ensuring the data is legally collected and processed. AI strategy alignment (A) is governance-related, not risk-critical. Escalation protocols (D) support incident response but come after confirming lawful processing.
References:
AAIA Domain 5: Data Privacy, Lawfulness of Processing
AAIA Domain 1: Privacy and Data Governance Programs

NEW QUESTION # 25
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