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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing AI | 8% | - Stakeholder management - Managing AI project teams and resources - Risk management in AI projects |
| Topic 2: CPMAI Methodology | 41% | - Phase VI: Iteration & Monitoring
|
| Topic 3: Data for AI | 13% | - Data strategy and governance - DataOps concepts - Data preparation and preprocessing |
| Topic 4: Trustworthy AI | 9% | - Privacy and security - Ethical considerations and bias - Transparency and explainability |
| Topic 5: AI Fundamentals | 16% | - Types of AI and Machine Learning - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations |
| Topic 6: Machine Learning | 13% | - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks - Supervised, Unsupervised, and Reinforcement Learning |
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. Your team is working on a new loan decision model that takes a number of factors and data points into consideration and then automatically approves or denies a loan. After a month in operation someone does a review and notices that the system is denying a large number of loans from a certain demographic when all other factors from people in other regions (such as age, salary, and credit score) are the same. What is most likely happening here?
A) Nothing is wrong, algorithmic decisions will never be 100%
B) Generative AI models hallucinating data results
C) Biased data sets leading to algorithmic discrimination
D) Data privacy issues leading to data sharing concerns
2. You are being tasked to manage an AI project at your company and you need to identify which project to start with. What's the best way to approach this?
A) Ask key stakeholders from your group and find a small problem that would have a big return on investment and start there.
B) Find a project that requires 100% accuracy in the results and start with that one.
C) Ask key stakeholders from all groups for input about their pain points.
D) Go through all possible scenarios to come up with the perfect first project.
3. A financial institution is planning to use AI capabilities to detect fraudulent transactions. The project manager needs to ensure that all necessary requirements are met before proceeding.
What is a necessary initial task?
A) Evaluating the accuracy of current fraud detection methods
B) Assessing the ethical implications of using AI for fraud detection
C) Determining the scalability of AI solutions for transaction monitoring
D) Identifying the primary stakeholders and their needs
4. An AI project team is assessing the scalability of a healthcare solution. Which factor should the project manager consider to help ensure the solution is scalable?
A) Human oversight requirements
B) Ability to handle increased loads
C) Integration with the existing infrastructure
D) Compliance with data regulations
5. Leadership wants a new HR system built that will better handle potential candidate matching. The project manager assigned to this project believes that the project is well-suited for AI, however they are unsure which pattern of AI this would be. What should the project manager do?
A) Move forward without determining which patter of AI this falls under.
B) Conduct a straw poll with stakeholders to determine which pattern of AI this project falls under so they can best collect the data needed and skill sets for the team.
C) Determine which pattern of AI this project falls under so they can best collect the data needed and skill sets for the team.
D) Pick an algorithm that seems best suited for the problem and then determine which pattern of AI it is based on the algorithm selected.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: C |






