Conduct AI Readiness Assessments CAIPM Practice Questions (Page 8)

Questions 36–40

1. 36application · medium

   A financial services firm's readiness assessment identifies three gaps: (1) insufficient training data for the AI model, (2) lack of a data privacy impact assessment process, and (3) low employee trust in AI decisions. The firm has a small budget and must comply with upcoming privacy regulations. Which gap should be prioritized?

   • AIncrease the volume of training data by purchasing external datasets.
   • BRun a company-wide campaign to build employee trust in AI.
   • CDelay all actions until the next fiscal year when more budget is available.
   • DEstablish a data privacy impact assessment process to meet regulatory requirements.
   Reveal Solution Discussion Select an answer first
2. 37expert · hard

   An insurance company's AI readiness assessment shows: strong data quality, but no clear data ownership; a culture that is innovative, but no AI governance; and a skilled IT team, but no business-side AI champions. The company wants to deploy an AI claims-processing system. Which gap is most critical to address first?

   • AAssign data owners for each dataset.
   • BBuild a proof-of-concept immediately.
   • CTrain business staff to become AI champions.
   • DEstablish AI governance to define roles, responsibilities, and accountability.
   Reveal Solution Discussion Select an answer first
4. 38expert · hard

   A healthcare organization's AI readiness assessment reveals three major gaps: (1) data privacy and governance policies are outdated, (2) clinical staff lack AI literacy, and (3) the IT infrastructure cannot support real-time inference. The organization has a limited budget and must comply with strict regulatory deadlines. Which gap should be prioritized first?

   • AUpgrade IT infrastructure to support real-time inference.
   • BUpdate data privacy and governance policies to meet regulatory requirements.
   • CRun a pilot project to test AI in a low-risk area first.
   • DTrain clinical staff on AI basics before any policy changes.
   Reveal Solution Discussion Select an answer first
5. 39expert · hard

   A retail chain's AI readiness assessment found: strong data science team, but no data governance; a culture that is risk-averse; and a legacy IT system that cannot support AI workloads. The company has a tight budget and wants to deploy an inventory optimization model. Which action should be prioritized?

   • ARun a change-management program to reduce risk aversion.
   • BImplement a data governance framework.
   • CHire more data scientists to accelerate model development.
   • DUpgrade the IT infrastructure to support AI workloads.
   Reveal Solution Discussion Select an answer first
6. 40expert · hard

   A hospital is assessing AI readiness for a clinical decision support system. The assessment team must collect data on clinician attitudes, the accuracy of electronic health records, and the security of the network. However, clinicians are overworked and unlikely to complete long surveys, and the IT team is wary of external auditors accessing patient data. Which assessment method mix best balances these constraints?

   • ARely solely on the IT team's self-assessment of data quality and security, and skip clinician input.
   • BConduct in-depth interviews with every clinician and a full external security audit with raw patient data.
   • CSend a lengthy survey to all clinicians and allow external auditors full access to patient records.
   • DUse short, anonymous pulse surveys for clinicians, a targeted data quality audit on de-identified records, and an internal security review with external guidance.
   Reveal Solution Discussion Select an answer first