Conduct AI Readiness Assessments CAIPM Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   When prioritizing actions to address readiness gaps, which two factors are most commonly considered?

   • ANumber of competitors and market share
   • BEmployee age and tenure
   • CImpact and feasibility
   • DColor and design preferences
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2. 22expert · hard

   A telecom company's readiness assessment reveals that its data science team is highly skilled, but the company lacks a centralized data platform, and the legal department has not approved any AI data-sharing agreements. The company has a tight deadline to launch a churn prediction model. The program manager must decide how to interpret and act on these findings. What is the best course of action?

   • APrioritize obtaining legal approval for data sharing, while starting a parallel effort to build a centralized data platform, and use a temporary data pipeline for the initial model.
   • BProceed with the model using data from a single business unit, and address the platform and legal gaps after launch.
   • CCancel the churn prediction project because the gaps are too large to overcome before the deadline.
   • DFocus only on building the centralized data platform, and ignore legal approvals until the platform is complete.
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4. 23expert · hard

   A manufacturing firm's readiness assessment shows that the plant floor has excellent IoT sensor data, but the corporate IT team lacks cloud experience, and the company has no formal AI risk management framework. The program manager must present findings to a board that is risk-averse and wants a clear business case. How should the report frame the findings to be most persuasive and actionable?

   • APresent the IoT data strength as a foundation, then clearly outline the IT skills and risk framework gaps, linking each to specific business risks and recommended actions.
   • BEmphasize the strength of the IoT data and downplay the IT skills and risk framework gaps to avoid alarming the board.
   • CLead with a detailed technical explanation of the IoT sensor architecture and data formats.
   • DRecommend immediate AI deployment because the data is ready, and address the gaps later.
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5. 24foundation · easy

   Which of the following is a key dimension typically evaluated in an AI readiness assessment?

   • ABrand logo design and marketing colors
   • BOffice location and employee commuting times
   • CData quality and availability
   • DCompany stock price and market capitalization
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6. 25application · medium

   A manufacturing company is assessing AI readiness for predictive maintenance. The program manager needs to understand the actual condition of legacy equipment sensors and the reliability of the data they produce, but the sensor documentation is outdated. Which assessment method is most appropriate for this specific need?

   • AConduct an on-site technical audit of the sensors, data logging systems, and network connectivity.
   • BDistribute a company-wide employee engagement survey about attitudes toward AI.
   • CInterview the IT helpdesk staff about recurring network issues.
   • DReview the company's AI strategy documents and past project reports.
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