Evaluate Initial AI Feasibility PMI-CPMAI Practice Questions (Page 1)

Questions 1–5

1. 1expert · hard

   A retail company wants to use AI to predict customer lifetime value. They have a large dataset of purchase history, but the data contains many duplicate records and inconsistent product codes. The company's marketing team is eager to use AI, but the IT team is concerned about data quality. The company has a limited budget for data cleaning. What should the company do to evaluate initial AI feasibility?

   • AFocus only on cleaning the data without considering alternative solutions.
   • BProceed with AI because the dataset is large, and AI can handle noisy data.
   • CHire a data cleaning consultant regardless of the cost.
   • DEstimate the cost and effort of cleaning the data, and compare it against the potential benefit of the AI model over a simple heuristic.
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   Which question is most relevant to a technical viability assessment?

   • ADoes the organization have executive sponsorship for the AI initiative?
   • BWill the AI solution reduce operational costs compared to manual processes?
   • CCan the AI model be integrated with the existing legacy CRM system?
   • DAre there enough data scientists available to develop the model?
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   During a technical viability assessment for a proposed AI solution, which factor is most directly evaluated?

   • AWhether the organization has sufficient skilled data scientists
   • BWhether the required data can be integrated with existing systems
   • CWhether the organization's culture supports adopting AI
   • DWhether the AI solution will be more cost-effective than a traditional approach
   Reveal Solution Discussion Select an answer first
5. 4expert · hard

   A financial services firm wants to use AI to detect money laundering. They have a large dataset of transactions, but only a tiny fraction are labeled as suspicious. The firm's compliance team is skeptical about AI and prefers traditional rule-based systems. The firm has a limited budget for data labeling. What is the most significant feasibility challenge?

   • AThe skepticism of the compliance team, which may resist adopting AI.
   • BThe lack of computational resources to train a model on the large transaction dataset.
   • CThe scarcity of labeled suspicious transactions, which may require expensive labeling or synthetic data generation.
   • DThe need to integrate the AI model with the existing transaction monitoring system.
   Reveal Solution Discussion Select an answer first
6. 5foundation · easy

   Which dimension is part of a data quality assessment?

   • ASpeed of data ingestion
   • BConsistency of the data across sources
   • CCost of storing the data
   • DVolume of data available for training
   Reveal Solution Discussion Select an answer first