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ISACA Advanced in AI Audit Questions 281–285 (page: 58)

Updated On: 12-Sep-2026

Which of the following is the MOST important change management control in an AI system?

  1. Scheduled retraining at fixed intervals
  2. Freezing of upstream data sources to prevent drift
  3. Standardized processing guide for all teams
  4. Version-controlled pipelines with lineage

Answer(s): D

Explanation:

Version-controlled pipelines with lineage provide traceability, reproducibility, and controlled change tracking across data, models, and processes, which is essential for managing updates, preventing uncontrolled modifications, and ensuring auditability and accountability in AI system change management.



Which of the following would be of GREATEST concern to an IS auditor assessing an AI model against data poisoning during model training?

  1. Data was generated synthetically.
  2. Data was taken from external sources.
  3. Data was introduced during pre-validation of the AI model.
  4. Data was introduced when fine-tuning the AI model.

Answer(s): B

Explanation:

Data sourced from external origins presents the highest poisoning risk because it introduces exposure to malicious manipulation, untrusted pipelines, and compromised integrity at the point of ingestion, which directly threatens model reliability and security during training.



Which of the following BEST contributes to the effectiveness of an organization’s AI change management?

  1. Adopting a traditional best practice framework for change management
  2. Engaging external consultants with specialized AI system expertise
  3. Requiring project team leaders to communicate the impacts of changes
  4. Applying a structured change approach tailored to AI implementation

Answer(s): D

Explanation:

A structured change approach tailored to AI implementation ensures that changes to data, models, pipelines, and dependencies are managed with AI-specific risks, lifecycle complexity, and governance requirements in mind, making change control effective, auditable, and resilient rather than generic or ad hoc.



An e-commerce organization uses an AI model to approve refunds.
Which of the following approaches BEST demonstrates effective supervision of the AI model’s decisions?

  1. Having employees review a sample of model decisions for accuracy
  2. Retraining the model daily to keep it up to date
  3. Using a second AI model to monitor and control decisions
  4. Logging all decisions made by the model

Answer(s): A

Explanation:

Human review of a sample of AI decisions provides direct oversight, enabling detection of errors, bias, or unintended behavior, and ensures accountability while validating that the model operates in line with business rules and policy objectives.



Which of the following represents the GREATEST challenge when introducing AI models in a production environment?

  1. Data complexity
  2. User training
  3. Infrastructure costs
  4. Model fine-tuning

Answer(s): A

Explanation:

Data complexity — variability in structure, quality, frequency, and sources — poses the greatest challenge because it directly impacts model performance, reliability, and maintainability in production, requiring robust preprocessing, integration, and validation controls to ensure operational effectiveness.



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