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PMI PMI-CPMAI Exam Questions

PMI PMI-CPMAI Exam Questions Answers

PMI Certified Professional in Managing AI

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PMI PMI-CPMAI Practice Test Questions ( Updated) – Real Exam Questions & Dumps PDF

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PMI PMI-CPMAI Sample Questions – Free Practice Test & Real Exam Prep

Question #1

A project manager is preparing a contingency plan for an AI-enabled underwriting platform. During outages, the business must still make time-sensitive decisions. What strategy best supports business continuity?

  • A. Implement a manual override process with defined escalation and decision rules 
  • B. Stop all underwriting until the AI system returns 
  • C. Keep the AI system running without monitoring to avoid interruptions 
  • D. Only increase marketing to offset the outage 
Answer: A
Question #2

A project team is evaluating whether an AI initiative should proceed beyond discovery. Stakeholders are aligned on objectives, but the team has not confirmed data access, quality, or legal constraints. What is the most appropriate next action? 

  • A. Begin model development using sample data 
  • B. Conduct a go/no-go assessment using readiness criteria 
  • C. Move directly to deployment planning
  •  D. Purchase additional compute infrastructure 
Answer: B
Question #3

A logistics company wants to use AI to optimize delivery routes for a client that runs a pizza franchise. Which AI capability should be used?

  • A. Autonomous systems
  •  B. Predictive analytics 
  • C. Conversational 
  • D. Hyperpersonalization 
Answer: B
Question #4

A city transportation department is deploying an AI model that adjusts traffic signal timing. The department is concerned that traffic patterns will shift seasonally and during major events. What is the best method to manage this risk after deployment?

  • A. Perform continuous monitoring and auditing for drift and performance degradation 
  • B. Increase the training dataset size once before launch 
  • C. Disable model updates to maintain consistent behavior 
  • D. Rely on vendor guarantees instead of internal controls 
Answer: A 
Question #5

A hospital project team is tasked with preparing patient telemetry data for a predictive maintenance AI model. They need to help ensure the data is in the right format and shape for the model. What should the project manager do to achieve these objectives?

  • A. Adopt a rule-based extraction, transformation, and loading (ETL) framework. 
  • B. Utilize an advanced data distribution service (DDS). 
  • C. Employ machine learning (ML) algorithms.
  •  D. Implement a batch processing system to enhance performance.
 Answer: A
Question #6

A healthcare organization is preparing training data for an AI model that predicts patient readmissions. The team discovers inconsistent coding across clinics for the same diagnosis. Which action best addresses the problem during data preparation?

  • A. Determine and apply data transformation and standardization steps 
  • B. Ignore the inconsistency because the model will learn patterns anyway 
  • C. Replace real data with only synthetic data 
  • D. Skip validation to save time 
Answer: A
Question #7

In a government healthcare AI project, the objective is to reduce patient wait times by optimizing staff schedules. After 6 months, the cost is US$500,000 with a completion rate of 60%. The project manager needs to determine the return on investment (ROI) to justify the current expenditure. What is an effective method to achieve this objective?

  • A. Utilize a net present value model to project future benefits. 
  • B. Calculate the total savings in patient wait times and compare them to the initial cost. 
  • C. Apply a cost-consequence analysis to measure project efficiency. 
  • D. Evaluate the incremental cost-benefit analysis using the cost-performance baseline. 
Answer: A
Question #8

A financial institution is implementing a new AI system for fraud detection. The project team must ensure the data meets the needs of the AI solution by verifying data quality, completeness, and relevance. They have access to various internal and external data sources. Which method addresses the project team's objectives?

  • A. Conducting a comprehensive data audit and cleansing process 
  • B. Limiting the data sources to internal databases to avoid complications 
  • C. Integrating data without improvement checks to expedite the project timeline 
  • D. Using pretrained models without tailoring to specific data 
Answer: A
Question #9

An IT services company project manager is creating an AI project scope statement. They need to include details on the environments, devices, and personnel that will use the AI solution. What should the project manager do?

  • A. Perform a detailed technical requirements audit for the scope statement. 
  • B. Develop a comprehensive usage scenario analysis. 
  • C. Gain stakeholder buy-in to proceed with the project.
  •  D. Create an AI efficacy program to complete the scope statement. 
Answer: B
Question #10

A project team is defining the requirements for an AI solution to ensure transparency in data selection and algorithm selection. The team needs to assess whether the AI solution is necessary and identify the cognitive parts of the project. What should the project manager do first?

  • A. Define the ethical concerns and transparency requirements. 
  • B. Evaluate non-cognitive alternatives and why they were ruled out. 
  • C. Determine the business objective and stakeholder needs. 
  • D. Identify the data sources and ensure compliance with regulations.
 Answer: C
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