ISACA Advanced in AI Audit AAIA Dumps in PDF

Free ISACA AAIA Real Questions (page: 10)

To ensure stakeholders are adequately prepared to address workforce impacts, which of the following is an IS auditor's BEST recommendation for an organization's AI incident response plan?

  1. Review the frequency of AI security incidents and updates to the response plan.
  2. Verify that the organization has an AI ethics committee to discuss potential workforce impacts.
  3. Validate that regular cross-functional AI incident drills and skill gap assessments are performed.
  4. Confirm that all employees have completed a standardized online AI awareness course within the last year.

Answer(s): C

Explanation:

Validating that regular cross-functional AI incident drills and skill gap assessments are performed is the best recommendation. This ensures stakeholders are prepared to handle workforce impacts by practicing coordinated responses and identifying areas requiring additional skills or training.



An organization seeks to sustain effective AI governance and risk management amid rapidly evolving AI technologies.

Which of the following represents the MOST effective course of action?

  1. Provide role-specific AI training to technical staff.
  2. Outsource AI training to external vendors.
  3. Conduct comprehensive AI training for senior management.
  4. Integrate continuous AI training into security awareness programs

Answer(s): D

Explanation:

Continuous AI training embedded into security awareness programs ensures that all stakeholders -- technical, managerial, and operational -- regularly update their knowledge as AI risks and technologies evolve. This supports sustained, organization-wide governance and risk management rather than limiting training to isolated groups or one-time events.



An AI tool is being implemented for a regional healthcare organization. Which of the following training methods BEST ensures the AI output does not reveal whether someone's personal data was used?

  1. Supervised learning with labeled patient records
  2. Data augmentation during training to improve privacy
  3. Differential privacy applied during model training
  4. Transfer learning using public health data sets

Answer(s): C

Explanation:

Differential privacy introduces controlled noise during model training, ensuring the model cannot reveal whether any specific individual's data was included in the training set. This provides strong protection against reidentification while maintaining model utility.



An organization has deployed a generative AI system for customer support that includes frequent updates to the AI model after deployment. Which of the following represents the GREATEST risk?

  1. Lack of a change management policy specific to AI
  2. Overreliance on manual review of AI model outputs
  3. Lack of continuous monitoring for model changes
  4. Lack of a dedicated AI governance committee

Answer(s): C

Explanation:

Frequent post-deployment model updates require continuous monitoring to detect drifts, errors, or unintended behaviors introduced by new versions. Without continuous monitoring, risks introduced by updates can go unnoticed, directly affecting reliability, safety, and compliance.



An organization is developing an AI system that integrates data from multiple external sources without clearly defined data ownership policies. Which of the following is the GREATEST concern in this situation?

  1. Deficiencies in policies and procedures validating AI model accuracy
  2. Limited documentation of user access permissions
  3. Excessive dependence on automated data collection and cleansing
  4. Gaps in AI privacy compliance and accountability

Answer(s): D

Explanation:

When data ownership is unclear across multiple external sources, the primary risk is noncompliance with privacy requirements and unclear accountability for how data is collected, used, and protected. This directly threatens AI privacy governance and regulatory adherence.



An organization is using a large language model (LLM) to assist in evaluating loan applications, but the training data used is known to be incomplete. Which of the following is the GREATEST associated risk?

  1. Unfair loan decisions
  2. Delays in loan approval
  3. Reduced customer satisfaction
  4. Increased manual processing of applications

Answer(s): A

Explanation:

Incomplete training data can cause the model to learn patterns that do not represent all applicant groups,
increasing the likelihood of unfair or biased loan decisions, which is the most significant governance and ethical risk.



Which of the following is the MOST important reason to establish AI governance structures that extend beyond regulatory compliance?

  1. To align with global AI data privacy standards
  2. To mitigate reputational risk associated with public scrutiny of AI systems
  3. To ensure ethical integrity throughout the AI life cycle
  4. To establish guardrails limiting AI system functionality to approved use cases

Answer(s): C

Explanation:

Establishing governance structures that go beyond compliance ensures ethical integrity across the AI life cycle, addressing fairness, accountability, and responsible use -- areas not fully covered by regulatory requirements but essential for trustworthy AI.



Which of the following should be an IS auditor's GREATEST concern when reviewing an anomaly detection process implemented for a high-risk AI system?

  1. Failure to identify anomalies that can bias training data
  2. Lack of regular quality reviews for training data
  3. Infrequent updates to anomaly detection algorithms
  4. Inadequate staff training on the use of the system

Answer(s): A

Explanation:

If anomalies that can bias training data go undetected, the AI system may learn incorrect or harmful patterns, directly compromising the integrity and reliability of a high-risk AI system. This poses the greatest governance and risk concern because biased training data affects all downstream model behavior.



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