Evaluate Initial AI Feasibility PMI-CPMAI Practice Questions (Page 4)

Questions 16–20

1. 16expert · hard

   A healthcare provider wants to use AI to analyze medical images for early detection of diabetic retinopathy. The provider has a large dataset of retinal scans, but the images are stored in a proprietary format that is not compatible with common AI frameworks. The IT team is small and lacks experience with image processing. The provider has a limited budget and cannot afford to hire external consultants. What is the most critical feasibility constraint?

   • AThe lack of integration with the hospital's existing PACS system.
   • BThe lack of GPU resources for training a deep learning model on the large dataset.
   • CThe lack of a data governance policy for medical images.
   • DThe incompatibility of the image format with AI frameworks, which may require significant effort to convert.
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   A bank wants to use AI to predict loan default risk. They have a large dataset of loan applications, but the data was collected from different branches with varying standards. Some branches recorded income in different currencies, and others omitted employment status. What is the most important feasibility concern?

   • AWhether the data can be standardized and cleaned to ensure consistency and completeness.
   • BWhether the bank can deploy the model on its mainframe systems.
   • CWhether the bank has enough loan applications to train a deep learning model.
   • DWhether the bank should use a traditional credit scoring model instead.
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A startup wants to build an AI-powered chatbot for customer support. They plan to train a large language model on their support tickets. The startup has a limited budget and no in-house GPU infrastructure. What should they evaluate to determine if the AI solution is feasible?

   • AThe cost and availability of cloud-based training resources, and whether the team has the skills to use them.
   • BWhether the support tickets are stored in a CRM system.
   • CWhether the chatbot can be integrated with the company's website.
   • DWhether the startup has a legal team to review AI-generated responses.
   Reveal Solution Discussion Select an answer first
5. 19foundation · easy

   Which factor is considered in an organizational readiness review?

   • AThe type of GPU hardware available
   • BThe number of data records available
   • CThe organization's data governance processes
   • DThe accuracy of the model on validation data
   Reveal Solution Discussion Select an answer first
6. 20application · medium

   A manufacturing company wants to use AI for real-time defect detection on a production line. The proposed model requires high-resolution image processing at 60 frames per second. The company's existing IT infrastructure is a small on-premises data center with limited GPU capacity. What should the company evaluate to determine if the AI solution is technically viable?

   • AWhether the company has enough labeled images of defects to train the model.
   • BWhether the required inference speed can be achieved with the available hardware or whether cloud-based processing is needed.
   • CWhether the production line workers are comfortable with AI monitoring their work.
   • DWhether the company can hire a data scientist to maintain the model after deployment.
   Reveal Solution Discussion Select an answer first