PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Identify Business Needs and Solutions | 26% | - Align AI initiatives with organizational strategy - Evaluate feasibility and value of AI solutions - Define requirements, scope, and success criteria |
| Support Responsible and Trustworthy AI Efforts | 15% | - Manage bias, risk, compliance, and societal impact - Establish ethical and governance frameworks - Ensure fairness, transparency, accountability |
| Manage AI Model Development and Evaluation | 16% | - Monitor performance, accuracy, and reliability - Address model drift, explainability, and limitations - Oversee model design, training, and validation |
| Operationalize AI Solution | 17% | - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch - Deploy AI systems into production |
| Identify Data Needs | 26% | - Define data requirements and sources - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure |
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. The team is evaluating where the sources of the data for training are. What phase of CPMAI are they in?
A) Phase III
B) Phase V
C) Phase IV
D) Phase VI
E) Phase I
F) Phase II
2. A retail organization wants to start an AI initiative because a competitor recently announced a machine learning platform. The project manager is asked to launch development immediately using an existing dataset.
What should the project manager do first?
A) Assemble a data science team and begin exploratory analysis
B) Procure a machine learning platform comparable to the competitor's
C) Define the specific business problem and measurable success criteria
D) Assess the quality and completeness of the existing dataset
3. A healthcare project manager is evaluating whether to implement an AI-powered diagnostic tool.
The initial cost is US$500,000 with an expected return on investment (ROI) of 15% within the first year. The project needs to satisfy multiple stakeholders including hospital administrators and medical staff. Which method will maximize a positive ROI for the AI implementation?
A) Ensuring all AI and non-AI components are integrated seamlessly.
B) Monitoring AI model performance against key performance indicators.
C) Acquiring alternatives to the AI solution as a contingency plan.
D) Seeking verbal commitments from interested parties at each project phase.
4. A consulting firm is preparing data for an AI-driven customer segmentation model. They need to verify data quality before data preparation. What should the project manager do first?
A) Apply data labeling techniques.
B) Assess data completeness.
C) Conduct data cleaning.
D) Implement data enhancement.
5. A project manager is evaluating whether an AI model is ready for operationalization. The project team has ensured the model meets accuracy and performance requirements and has conducted extensive testing. However, uncertainty about the model's operationalization in different environments and its compliance with regulatory standards still exists. What should the team do next?
A) Implement additional noncognitive solutions.
B) Evaluate the model's adaptability to diverse conditions.
C) Consider retraining the model for better performance.
D) Reassess the project's data preparation phase.
Solutions:
| Question # 1 Answer: F | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: B |
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