Define Success Criteria (e.g., KPIs, Metrics) PMI-CPMAI Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Why is it important for technical performance targets to be realistic and aligned with business requirements?

   • ATo reduce the need for data validation
   • BTo increase the number of training epochs
   • CTo make the model more complex and difficult to understand
   • DTo ensure the model can be deployed and used effectively in the business context
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2. 7foundation · easy

   Which of the following is the best example of a measurable performance indicator for an AI model designed to classify customer support tickets?

   • AThe subjective opinion of the development team
   • BThe programming language used to implement the model
   • CThe number of tickets in the training dataset
   • DThe model's accuracy on a held-out validation set
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4. 8foundation · easy

   Which of the following best describes a business impact metric for an AI solution?

   • AA metric that records the version of the AI framework used
   • BA metric that quantifies the value delivered to the business, such as cost savings or revenue increase
   • CA metric that counts the number of data scientists on the team
   • DA metric that measures the model's training time
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5. 9expert · hard

   A streaming service is deploying an AI model to recommend movies. The product team wants to maximize user engagement, but the engineering team warns that the model's inference latency is too high for real-time recommendations. The model currently has a latency of 500ms per request, and the engineering team has a target of 200ms. Which approach best defines the technical performance benchmarks?

   • ASet the latency target to 500ms and focus only on improving quality
   • BSet a hard quality target (e.g., precision@10) and accept any latency
   • CSet a hard latency target of 200ms and accept any impact on recommendation quality
   • DDefine a latency budget that allows for a small degradation in quality, with a minimum quality threshold
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6. 10application · medium

   A retail company is deploying an AI model to predict daily store foot traffic for staffing optimization. The operations team wants to reduce labor costs while maintaining customer service. Which set of success criteria best measures the model's business impact?

   • AModel accuracy (e.g., RMSE) and the percentage reduction in labor cost per store
   • BModel training time and the number of stores using the model
   • CThe total number of predictions made per day and the model's uptime
   • DCustomer satisfaction survey scores and model inference latency
   Reveal Solution Discussion Select an answer first