Develop AI Project Scope Statement PMI-CPMAI Practice Questions (Page 3)

Questions 11–15

1. 11expert · hard

   An e-commerce company is implementing an AI system to personalize product recommendations. The project sponsor wants to increase average order value by 15%. The data science team has built a model that recommends products based on browsing history. The marketing team is concerned that the model may recommend out-of-stock items, leading to customer frustration. The project manager is defining success criteria. Which success metric is most appropriate?

   • APercentage of recommendations that are in stock
   • BCustomer click-through rate on recommendations
   • CIncrease in average order value by 15%
   • DModel accuracy on product recommendations
   Reveal Solution Discussion Select an answer first
2. 12foundation · easy

   When the available resources are insufficient to deliver the full AI project scope, what is an appropriate action?

   • AProceed with the full scope and hope resources become available later
   • BIgnore the resource limitation and focus only on technical requirements
   • CRemove all success criteria to simplify the project
   • DAdjust the scope to align with the available resources and business priorities
   Reveal Solution Discussion Select an answer first
4. 13expert · hard

   A multinational bank is developing an AI system for credit scoring. The project team has access to customer data from multiple countries. The legal team has stated that the model must comply with the EU's General Data Protection Regulation (GDPR), which restricts the use of certain personal data. The project manager is documenting assumptions and constraints. Which item should be documented as a CONSTRAINT?

   • AThe model must comply with GDPR requirements
   • BThe model will be deployed in the bank's data center
   • CThe project team has experience with credit scoring models
   • DThe model will be trained on historical customer data
   Reveal Solution Discussion Select an answer first
5. 14application · medium

   An insurance company is developing an AI system to automate claims processing. The project sponsor wants the system to reduce the average claims processing time from 10 days to 3 days. The data science team notes that the model's precision must be high to avoid incorrectly denying valid claims. The project manager is defining success criteria. Which combination of metrics best captures the project's success?

   • AAverage processing time and model precision
   • BCost per claim and model training time
   • CCustomer satisfaction score and system uptime
   • DModel accuracy and the number of claims processed
   Reveal Solution Discussion Select an answer first
6. 15application · medium

   A logistics company is implementing an AI model to predict delivery delays. The operations director wants the model to flag at-risk shipments so dispatchers can re-route them. The project manager is defining success criteria. Which success metric is most appropriate for evaluating the model's business value?

   • AThe model's accuracy on historical delivery data
   • BThe time required to train the model on a new dataset
   • CThe number of data sources integrated into the model
   • DThe percentage of flagged shipments that are successfully re-routed and arrive on time
   Reveal Solution Discussion Select an answer first