Assess AI Readiness Across Key Dimensions CAIPM Practice Questions (Page 4)

Questions 16–20

1. 16application · medium

   A hospital wants to implement AI-assisted clinical decision support. The physicians are concerned about liability and the accuracy of AI recommendations. The hospital has a robust IT infrastructure and clean data, but the clinical workflow is already overloaded. What is the most significant people/culture readiness barrier?

   • APhysicians' lack of trust in AI recommendations
   • BInsufficient data quality
   • CLack of computing power
   • DPoorly defined clinical workflows
   Reveal Solution Discussion Select an answer first
2. 17foundation · easy

   Which of the following is a benefit of using a recognized AI readiness assessment model?

   • AIt eliminates the need for data collection
   • BIt enables benchmarking against industry standards and best practices
   • CIt ensures that all AI projects will be profitable
   • DIt automatically selects the best AI technology for the organization
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A logistics company wants to deploy an AI route optimization system. The company's existing servers are outdated, and the data is stored in on-premises databases with no cloud connectivity. The IT team has limited experience with AI deployment. The budget is tight, and the project must start within three months. What is the most critical technology readiness gap to address?

   • AInadequate compute and storage infrastructure for AI workloads
   • BLack of a data governance policy
   • CNo AI-specific programming language expertise
   • DInsufficient training data for route optimization
   Reveal Solution Discussion Select an answer first
5. 19application · medium

   A retail chain is considering AI for demand forecasting. The CEO wants a quick go/no-go decision, but the company has never used AI and lacks a clear data strategy. You need to provide a structured assessment that covers multiple dimensions and produces a prioritized action plan. Which approach best fits this need?

   • AUse an established AI readiness framework to score strategy, data, technology, people, and processes, then identify gaps and prioritize actions.
   • BAsk the IT department to evaluate the current data infrastructure.
   • CRun a cost-benefit analysis on the forecasting use case alone.
   • DBenchmark against a competitor's AI implementation.
   Reveal Solution Discussion Select an answer first
6. 20expert · hard

   A financial services firm wants to use AI for credit risk modeling. The firm has a large amount of historical data, but it is stored in a legacy mainframe system. The data is complete but not easily accessible. The firm has a strict budget and cannot afford a major data migration. What is the most practical approach?

   • ACreate a data lake on low-cost storage and periodically extract data from the mainframe.
   • BManually export data from the mainframe to spreadsheets for analysis.
   • CUse the legacy system's APIs to feed data directly into the AI model.
   • DExtract and transform the data into a modern data warehouse for AI use.
   Reveal Solution Discussion Select an answer first