Real PMI CPMAI practice exam questions for easy pass!
Updated: Aug 04, 2026
No. of Questions: 272 Questions & Answers with Testing Engine
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| Certification Vendor: | Project Management Institute (PMI) |
| Exam Name: | PMI Cognitive Project Management in AI (PMI-CPMAI) Certification Exam |
| Exam Number: | PMI-CPMAI |
| Related Certifications: | PMP® PMI-ACP® PMI-RMP® PMI-SP® |
| Exam Format: | Multiple-choice, Scenario-based, Application-focused |
| Certificate Validity Period: | Valid indefinitely; requires 30 PDUs every 3 years for maintenance |
| Exam Price: | USD 699 (PMI Member), USD 899 (Non-Member) |
| Available Languages: | English |
| Passing Score: | Pass/Fail; no fixed numerical score published |
| Exam Duration: | 160 minutes |
| Real Exam Qty: | 120 (100 scored, 20 unscored pretest) |
| Recommended Training: | PMI-CPMAI Exam Prep Course |
| Exam Registration: | Pearson VUE Scheduling PMI Official Registration |
| Sample Questions: | PMI CPMAI Sample Questions |
| Exam Way: | Computer-based test (CBT) at Pearson VUE test center or online proctored |
| Pre Condition: | Completion of official PMI-CPMAI Exam Prep Course required; no prior experience or other certifications mandatory |
| Official Syllabus URL: | https://www.pmi.org/certifications/ai-project-management-cpmai |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Manage AI Model Development and Evaluation | 16% | - Monitor performance, accuracy, and reliability - Oversee model design, training, and validation - Address model drift, explainability, and limitations |
| Topic 2: Identify Business Needs and Solutions | 26% | - Evaluate feasibility and value of AI solutions - Align AI initiatives with organizational strategy - Define requirements, scope, and success criteria |
| Topic 3: Operationalize AI Solution | 17% | - Deploy AI systems into production - Manage change, adoption, and governance post-launch - Establish monitoring, maintenance, and improvement processes |
| Topic 4: Support Responsible and Trustworthy AI Efforts | 15% | - Ensure fairness, transparency, accountability - Establish ethical and governance frameworks - Manage bias, risk, compliance, and societal impact |
| Topic 5: Identify Data Needs | 26% | - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure - Define data requirements and sources |
1. A project team is working on an AI initiative that requires ensuring the explainability and transparency of their selected algorithms. They have identified the business requirements and stakeholders. What is an effective way to address the project objectives?
A) Leveraging generative AI for advanced data analysis
B) Adopting a principle of least privilege for data access
C) Implementing a chain-of-thought prompting technique
D) Using a rule-based approach to maintain simplicity
2. A company is evaluating whether to implement AI for a project. They have defined their business objectives and determined the AI capability they want to use. Which action will enable the project manager to move forward with the project?
A) Conducting a data quality assessment
B) Implementing a preliminary version of the AI solution
C) Conducting a go/no-go assessment
D) Identifying the contingency procedures
3. You're running an AI project and want to speed up training of the model so that you can complete your current CPMAI iteration within the two-week timeframe the team has set. What's one approach to speed up model training?
A) Use cloud-based technology
B) Use Brute force method
C) Use or extend a pre-trained model
D) Use data from a previous project
4. You've built your model and now need to see if it actually works as expected. In which phase of CPMAI is this done?
A) Phase II
B) Phase III
C) Phase IV
D) Phase I
E) Phase V
F) Phase VI
5. An energy technology firm is developing an AI model to predict energy consumption patterns.
They need to gather the required data from smart meters, weather forecasts, and historical usage records. To help ensure the AI model performs well, which action will address their needs?
A) Utilizing a data lake to store and process all data sources
B) Adopting a hybrid cloud approach for scalable data management
C) Integrating a data warehouse with real-time data ingestion
D) Leveraging federated learning to keep data decentralized
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: E | Question # 5 Answer: C |
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