AI Use Case Identification and Value Prioritization CAIPM Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A retail company's IT team proposes an AI chatbot for customer support, but the customer service department is concerned about job losses and quality issues. The AI program manager needs to gain buy-in. Which approach is most effective?

   • AExplain that AI is inevitable and the company must adopt it to remain competitive
   • BPresent a detailed cost-benefit analysis showing long-term savings from reduced headcount
   • CProceed with a pilot and report results to the customer service team after it is successful
   • DInvolve customer service representatives in co-designing the chatbot to augment their work, not replace it
   Reveal Solution Discussion Select an answer first
2. 12application · medium

   A telecommunications company wants to reduce customer churn. The marketing team suggests AI for personalized offers, while the network team suggests AI for predictive maintenance. The company has rich customer usage data but limited sensor data from network equipment. Which use case is more viable in the short term?

   • APersonalized offers, because customer usage data is readily available and sufficient for modeling
   • BPredictive maintenance, because it addresses a critical operational need
   • CNeither, because the company should first invest in data collection for both use cases
   • DBoth, because they are independent and can be developed concurrently
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4. 13application · medium

   A hospital is prioritizing AI use cases. The clinical staff wants AI for diagnostic support, while the administrative staff wants AI for scheduling optimization. The hospital's strategic goal is to improve patient outcomes. The clinical use case has higher strategic alignment but requires more data and regulatory approval. What should the AI program manager do?

   • APrioritize the clinical use case but plan for a longer timeline due to regulatory and data requirements
   • BPrioritize the scheduling use case because it is faster and easier to implement
   • CAsk the clinical staff to justify the use case with more evidence
   • DPrioritize both equally to satisfy both stakeholder groups
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5. 14application · medium

   A media company wants to implement an AI content-recommendation system. The company has a large data engineering team but no dedicated data scientists. The content metadata is well-structured, but user interaction data is sparse. The program manager must assess resource feasibility. What is the most significant resource constraint for this use case?

   • ATechnology, because the company lacks the compute infrastructure for training large models.
   • BData, because sparse user interaction data makes it difficult to train a personalized recommendation model.
   • CMetadata quality, because poorly structured content metadata will degrade recommendations.
   • DTalent, because the company lacks the data science skills needed to build and tune the recommendation model.
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6. 15foundation · easy

   In a phased AI roadmap, why might a use case be scheduled in a later phase even if it has high value?

   • ABecause it depends on data or systems that will be delivered by an earlier use case
   • BBecause the use case has no stakeholders
   • CBecause high-value use cases are always implemented last
   • DBecause the organization wants to avoid delivering any value early
   Reveal Solution Discussion Select an answer first