
EC-CouncilCertified AI Program Manager
Domain 3Objective 3
AI Strategy and Adoption Roadmap Design CAIPM Practice Questions (Page 3)
Part of the AI Use Case Identification and Strategy Design domain, which makes up ~18% of our current practice bank.
52questions here
11free pages
10concepts
Questions 11–15
- 11
In the iterative implementation approach, what typically happens after a successful pilot?
Select an answer first - 12
A manufacturing company has identified three AI use cases: (1) predictive maintenance for critical machinery, (2) automated quality inspection on the production line, and (3) a chatbot for internal HR queries. The company has limited data science resources and a strict budget. The predictive maintenance use case has high business value but requires significant sensor data integration; the quality inspection use case has moderate value and can use existing camera data; the chatbot has low value but is easy to implement. Which use case should the program manager prioritize first?
Select an answer first - 13
A manufacturing company has three proposed AI use cases: (1) predictive maintenance on factory equipment, (2) automated supplier-contract review, and (3) a customer-facing chatbot. The predictive-maintenance project requires new IoT sensors and has a 14-month payback. The contract-review project can use existing document data and has a 6-month payback but touches sensitive legal information. The chatbot has high visibility but low expected cost savings. The company has a limited budget and a risk-averse legal team. Which use case should be prioritized first?
Select an answer first - 14
A media company has deployed an AI system for content recommendation. The initial KPIs show a 20% increase in user engagement, but the content team is concerned that the AI is promoting low-quality content. The program manager must define KPIs for the next phase. Which KPI set best balances engagement with content quality?
Select an answer first - 15
During an AI adoption readiness assessment, which factor evaluates whether the organization has sufficient quality and volume of data to train AI models?
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