ISACA AAIA Exam Prep
ISACA Advanced in AI Audit (Page 33 )

Updated On: 10-Sep-2026

An AI healthcare diagnostic tool requires large volumes of patient data, raising concerns about privacy and data breaches.
Which of the following is the MOST effective strategy to mitigate this risk?

  1. Encrypt the data and transmit it through a secure channel.
  2. Limit the tool's access to only publicly available data sets.
  3. Collect data from all patients to use for data analysis.
  4. Use synthetic data or anonymized data sets for model training.

Answer(s): D

Explanation:

Using synthetic or anonymized data minimizes the exposure of identifiable patient information while still allowing the model to be trained effectively. This approach most effectively reduces privacy and breach risks compared to securing transmission or limiting data sources.



Which of the following is MOST important to consider when evaluating ethical risk related to data used for training an AI model?

  1. Ability to generate diverse outputs
  2. Sensitivity and origin of training data
  3. Frequency of model updates
  4. Cleaning and validation methods for training data

Answer(s): B

Explanation:

Ethical risk is primarily driven by the sensitivity and origin of training data, as these factors determine whether the data was collected appropriately, used with consent, and processed in a way that avoids harm, discrimination, or privacy violations.



Which of the following is the GREATEST concern when an audit team relies on generative AI to create audit reports?

  1. The reports may be more likely to reflect outdated information.
  2. The reports may contain misstatements resulting from hallucinations.
  3. The reports may use inconsistent formatting from prior audit findings.
  4. The reports may tend to use generic language for audit issues.

Answer(s): B

Explanation:

Generative AI can produce hallucinations — fabricated or incorrect statements — which can lead to inaccurate audit reports. This poses the greatest concern because it directly compromises the reliability and integrity of the audit’s conclusions.



Which of the following is the MOST important reason to conduct regular threat modeling exercises for AI systems and data?

  1. To proactively identify potential vulnerabilities in AI systems
  2. To assess the performance of AI algorithms
  3. To comply with AI regulatory requirements
  4. To prevent instances of AI model drift

Answer(s): A

Explanation:

Threat modeling enables proactive identification of vulnerabilities specific to AI systems and their data flows, allowing organizations to address security risks before they are exploited. This directly strengthens AI governance and risk management.



Which of the following is the MOST important reason for applying regular software updates to AI systems operating in high-risk environments?

  1. To safeguard the systems against AI-powered zero-day exploits
  2. To accelerate model training cycles and enhance processing speed
  3. To reduce the need for human oversight of model outputs
  4. To address vulnerabilities and reduce the risk of output integrity attacks

Answer(s): D

Explanation:

Regular software updates are essential in high-risk AI environments because they address security vulnerabilities and protect the system from attacks that could compromise output integrity. Ensuring the reliability and trustworthiness of AI outputs is the primary governance concern.



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