A retail organization uses an AI model to forecast inventory based on customer purchasing trends and updates the model quarterly. The model recently failed to recognize a surge in demand during a popular shopping season. Which of the following issues does this situation BEST demonstrate?
Answer(s): A
This situation best demonstrates data drift, where the input data patterns have changed over time — such as seasonal demand shifts — not reflected in the AI model. Since the model is only updated quarterly, it likely missed recent trends, leading to inaccurate forecasts.
When auditing an AI model, an IS auditor notices that the controls over transactional processes are inadequate. Which of the following should the auditor recommend to BEST reduce these risks?
Answer(s): D
Implementing human-in-the-loop processes ensures that human oversight can detect and correct errors in transactional processes where AI controls are inadequate. This directly reduces operational risks by adding a safeguard against faulty or biased AI outputs.
An AI system is misclassifying images after a routine model update. An IS auditor discovers that the updated model file was replaced by an unauthorized version. Which of the following is the auditor’s BEST recommendation?
Reverting to the last verified model version restores system reliability quickly, while initiating a root cause analysis addresses the unauthorized replacement and prevents recurrence. This balances immediate risk mitigation with long-term operational assurance.
During an audit of an AI solution, the modeler informs the IS auditor that data augmentation techniques were utilized. Which of the following BEST enables the auditor to determine the effectiveness of the data augmentation?
Answer(s): B
Comparing the performance metrics of the model before and after augmentation best determines the effectiveness of data augmentation. This directly shows whether the augmentation improved model accuracy, generalization, or robustness in practice.
An organization's deployed AI model exhibits model drift. Which of the following is the BEST way to mitigate this issue?
Answer(s): C
Implementing continuous monitoring and retraining mechanisms is the best way to mitigate model drift. This ensures the model adapts to changing data patterns over time, maintaining accuracy and reliability in production.
Post your Comments and Discuss ISACA AAIA exam prep with other Community members:
Our website is free, but we have to fight against AI bots and content theft. We're sorry for the inconvenience caused by these security measures. You can access the rest of the AAIA content, but please register or login to continue.