Free AAIA Exam Braindumps
ISACA Advanced in AI Audit Questions 256–260 (page: 53)

Updated On: 12-Sep-2026

Which of the following is the MOST important key indicator to assess when auditing the deployment of AI in predictive maintenance system in manufacturing operations?

  1. Percentage of AI’s predictive algorithms that are compliant with industry standards
  2. Frequency of updates to AI predictive models based on equipment usage
  3. Reduction in downtime and maintenance costs due to AI use
  4. Total number of predictive maintenance scenarios implemented using AI

Answer(s): C

Explanation:

The most important key indicator is the reduction in downtime and maintenance costs due to AI use. This directly measures the effectiveness and business value of the predictive maintenance system in manufacturing operations.



Which of the following is the BEST reason that recurrent neural networks enable language translation of documents?

  1. The process is sequential.
  2. The process uses association rules.
  3. The process is specialized for grid data.
  4. The process is unidirectional.

Answer(s): A

Explanation:

Recurrent neural networks handle sequential data by retaining information from earlier inputs, making them well-suited for tasks like language translation where understanding word order and context across a sequence is essential.



Which of the following is the BEST way to mitigate data poisoning in an AI model?

  1. Rely on external third-party model providers.
  2. Increase training data set size.
  3. Implement robust data validation protocols.
  4. Use simpler algorithms to improve explainability.

Answer(s): C

Explanation:

Robust data validation protocols help detect and prevent malicious or corrupted data from entering the training pipeline, directly reducing the risk of data poisoning attacks.



An IS auditor reviewed an AI-enabled software for processing a bank’s financial information and discovered errors in the training data.
Which of the following would BEST mitigate this risk?

  1. Functional testing of the application
  2. Data quality testing
  3. User interface testing
  4. Model validation on benchmark data

Answer(s): B

Explanation:

Data quality testing directly addresses errors in the training data by validating completeness, accuracy, and integrity, thereby reducing the risk of incorrect model behavior caused by flawed inputs.



Which of the following types of AI can use unlabeled data sets to imitate human learning behavior?

  1. Supervised learning
  2. Federated learning
  3. Reinforcement learning
  4. Unsupervised learning

Answer(s): D

Explanation:

Unsupervised learning enables AI models to learn patterns and structures directly from unlabeled data, allowing them to imitate aspects of human exploratory learning without predefined outputs.



Viewing page 53 of 113
Viewing questions 261 - 265 out of 556 questions


Post your Comments and Discuss ISACA AAIA exam prep with other Community members:

AI Tutor AI Tutor 👋 I’m here to help!