The future of project management is AI-driven. With the Certified Professional in Managing AI (PMI-CPMAI) Certification, project managers and professionals gain the structured methodology needed to lead Artificial Intelligence (AI), Machine Learning (ML), and cognitive technology initiatives to success.
Developed by Cognilytica and now endorsed by PMI, this globally recognized AI project management certification helps you build future-ready skills and stay ahead in a market where AI expertise is the most in-demand competency.
The PMI’s acquisition of Cognilytica has strengthened PMI’s advanced AI resources for project managers, enabling them to achieve success in implementing AI. Cognilytica provided best practices, certification, and training through its flagship CPMAI Certification course.
Now, PMI is offering this prime certification under its banner for project professionals working towards organizational AI initiatives.
Unlike traditional certifications, PMI-CPMAI is:
AI-Specific – Created exclusively for AI, ML, and Data Science projects.
Data-Centric – Focuses on data as the foundation of AI project success.
Vendor-Neutral – Applicable across industries, tools, and platforms.
Globally Endorsed – Recognized by PMI, the world’s largest project management association.
Mrs. Vaijayanthee Kamat is a project management expert with 37+ years of experience leading large-scale global projects and programs across industries such as Pharma, Food, Textile, Engineering, and IT. She has successfully delivered multiple ERP implementations, including SAP upgrades, and is the vision behind Global SAP Support. She will be leading the CPMAI training at ProThoughts.
Training, mentoring, and life coaching are her passions, which she actively pursues to create impact. Vaijayanthee is also the co-founder of two project management institutes (EPMA & EPMC).
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Contact: Ms Aditi Posam
WhatsApp us : +91 9867173114
Email id – aditi@prothoughts.co.in
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The trainer maintained a perfect balance between concept explanation, interactive discussions, and hands-on exercises. They were always approachable, encouraged questions, and ensured that everyone in the group understood the material thoroughly before moving on.
Gandhar Bhole
I had a great experience of learning the key and essential concepts of Project Management. I would definitely love to apply all these concepts in my day to day work life. Thanks to Prothoughts and our trainer
Industry Demand
<Fastest-growing field in project management>
<78% of companies use AI in at least one business function>
<Cross-industry need for AI-savvy project leaders>
<Skills gap between traditional PM and AI initiatives>
What You’ll Learn with CPMAI?
<AI Foundations made practical>
<Structured AI project methodology>
<Data & model management essentials>
<Lead cross-functional AI teams>
Who Is It Ideal For?
<Project Managers - Bridge the gap between traditional project practices and AI project initiatives>
<Data Professionals - Combine data expertise with structured AI project methods>
<Tech Leaders - Lead AI initiatives aligned with business goals>
<Learning and Development Leaders - Drive organizational AI adoption and team upskilling>
CPMAI Course Curriculum
To earn the CPMAI Certification, you must be fluent in the CPMAI methodology. The methodology itself covers best practices for Artificial Intelligence (AI) and Machine Learning (ML), data analytics, and intelligent automation for all types of projects. Thus, it is only imperative that the CPMAI learning modules reflect the coursework of the methodology.
The CPMAI curriculum is carefully designed to take you from foundational AI knowledge to advanced project implementation. The CPMAI exam preparation course is structured into seven focused modules, each organized around the six-phase CPMAI Methodology. Each module addresses a key domain for today’s AI-driven workplace.
Module 1: The Need For AI Project Management
This module will set the foundation for the need for AI in project management. It explores why AI projects struggle and how AI-specific project management techniques can improve outcomes.
Learning Outcome: You’ll get an overview of current AI projects, the concerned gap, and the scope of structured AI project management practices.
Module 2: Matching AI with Business Needs
It follows Phase 1 of the CPMAI Methodology (Business Understanding). After the introduction, the groundwork is to define the business needs, and then add business opportunities where AI can add measurable value. The focus of this module is to help you strategically align your business with AI. Learning Outcome: You’ll learn how to define use cases, create business cases for AI, assess feasibility, and ensure alignment with organizational goals and ROI expectations.
Module 3: Identifying Data Needs for AI Projects
Aligned with Phase 2 of the CPMAI Methodology (Data Understanding). This module aims to bridge the gap between business problems and the data that will guide AI in providing tailored-made solutions for your organization. Learning Outcome: You’ll learn how to identify, collect, and evaluate data sources, ensuring they align with your business objectives and AI project goals.
Module 4: Managing Data Preparation Needs for AI Projects
Aligned with Phase 3 of the CPMAI Methodology (Data Preparation). This module focuses on preparing, cleaning, and transforming data to ensure it is accurate, complete, and ready for AI model development. Learning Outcome: You’ll learn best practices for data preparation, feature engineering, and governance to ensure your AI models are built on a reliable foundation.
Module 5: Iterating Development and Delivery of AI Projects
Aligned with Phase 4 of the CPMAI Methodology (Model Development). This module covers the iterative development of the AI models and refining them through experimentation, testing, and continuous feedback sprints.
Learning Outcome: You’ll learn to understand agile model development cycles, and also understand key metrics to track performance and ensure the models meet business and technical expectations.
Module 6: Testing and Evaluating AI Systems
Aligned with Phase 5 of the CPMAI Methodology (Model Evaluation). This module will focus on evaluating AI systems for both technical performance and business relevance, ensuring ethical, fair, and accurate results before deployment. Learning Outcome: You’ll learn how to validate AI models, assess for accuracy, test bias, and finally confirm if the system meets business and ethical standards.
Module 7: Operationalizing AI
Aligned with Phase 6 of the CPMAI Methodology (Model Operationalization). This module focuses on positioning AI systems into operations and establishing frameworks for monitoring, maintaining, and continuous improvement. Learning Outcome: You’ll learn to instill the AI model into your organization’s operation and create the best practices for AI adoption, along with sustainable solutions that deliver value for the business.
CPMAI Training by ProThoughts Features
Get Trained from PMI’s Premier ATP - Official PMI-authorized instruction.
Personalized Support & Mentorship - Direct access to expert mentors and best consultants.
Applied Learning with AI-Focused Case Studies - Real-world AI project scenarios.
Learning Designed for Busy Professionals - Flexible learning for working professionals.
As a Premier Authorized Training Partner (ATP) of PMI, ProThoughts provides official PMI learning material as part of the CPMAI course. In addition, you’ll receive:
Practice questions and mock exams to test your knowledge
Flashcards for quick revision
Supplementary study resources for a self-paced learning.
The program is designed to be interactive, with engaging exercises to simplify complex concepts.
The course is led by our in-house expert instructor, Mrs. Vaijayanthee Kamat, a highly respected project management trainer with 15+ years of experience. She is currently pursuing a Ph.D. in Artificial Intelligence, and she brings unique academic depth and industry insights to the workshop.
Upon completing the CPMAI course training and examination, you can earn a total of 21 PDUs. You can use these PDUs towards maintaining your other PMI credentials.
The CPMAI exam has 100 questions to be attempted in 2 hours (120 minutes). Please note that there is no scheduled break for this exam. Out of the 100 questions, 10 are considered pre-test questions. Pre-test questions do not affect the score and are used in examinations as an effective and legitimate way to test the validity of future examination questions. All questions are placed throughout the examination randomly.
The CPMAI exam will test your knowledge across the 6 domains as listed in the PMI’s CPMAI Exam Content Outline. The six domains are AI Fundamentals (16%), CPMAI Methodology (41%), Machine Learning (13%), Data for AI (13%), Managing AI (8%), and Trustworthy AI (9%). Additionally, all the domains are interlinked, so do not avoid any domain during your exam prep. (Note: The percentage stated above is the weightage of each domain in the CPMAI Certification Exam.)
No. This course has no prerequisites. CPMAI v7 does not require any prior work experience, technical knowledge, or AI experience, certifications, or requirements to take the course. The course starts with AI fundamentals and builds knowledge tailored to managing AI initiatives from a project management perspective. Although familiarity with Project management or IT is helpful, it’s not mandatory.
Critical path is used to start and finish a project, but in CPMAI, it is continuously monitored rather than considered complete and done. Regarding risk, CPMAI has six phases. For example, if you are in phase 4 (model development) and realize you need better or additional data, you go back to phase 2 (data preparation) and then return to phase 4. This iterative approach reduces the probability of AI not performing well. Priority is determined in phase 1 itself.
No, you do not need any technical knowledge of AI, ML, or Generative AI for this certification. It is interesting to learn about, but prior technical knowledge is not required.
While CRISP-DM originated in the late 1970s and has not been updated since 1999, CPMAI does not use CRISP-DM as-is. It is based on the CRISP-DM framework but CRISP-DM lacks AI-centric features. PMI has built six phases on top of the CRISP-DM foundation to make CPMAI specifically applicable for AI and ML projects.
Yes, you need to attend, because CPMAI is different. What you learned in the PMP program focuses on general project management and is not sufficient for this specific certification. You will need to go through the training again.
CPMAI™ v7 is the main course we will be working on. CPMAI™+E v7 covers additional topics, such as ethics, and includes extra questions. Once you are certified in version 7, you can take the +E version, but it is not required.
Yes, you will receive PDUs for the CPMAI course training. If you are taking the training for CPMAI certification, the PDUs are primarily used for that certification. If you choose not to take the CPMAI exam, these PDUs can also be applied towards other PMI certifications, such as renewing your PMP.
CPMAI is relatively new, but the CPMAI framework originates from CRISP-DM, which is well-known, tested, and appreciated in the industry. Right now, there is a strong need for a framework that can streamline AI projects, and CPMAI provides exactly that. Being certified in this framework adds value, and since it is now a PMI certification, it carries recognition and credibility in the market.
CPMAI is used for AI projects, while MS Project is simply a tool to help plan and manage a project. Not every project requires CPMAI, but if your project involves creating an AI model, building a chatbot for your website, or offering a personalised shopping experience, then CPMAI is usable. Since AI is highly dependent on data, you will need to work with large amounts of data across all phases. Traditional PMP is not sufficient because it focuses on general project management, whereas CPMAI is tailored specifically for AI projects.
It could be around 2 to 4 days, depending on the approach. Rushing through it is not recommended, and the duration will also depend on how much participants want to learn and how deep they want to go.
Yes, it does. Model development is just the result. Beyond that, you need to continuously monitor and manage the AI project. CPMAI focuses on AI project management specifically, not general or traditional project management.
The data does not improve by itself. Any data you work on, whether it is accurate or contains errors, can be corrected, but it does not improve automatically.
Governance and compliance are not limited to a single phase; they span all phases of an AI project. During data collection and planning, you need to consider governance. While preparing and getting the data ready, governance and compliance remain important. During execution, aspects like data privacy and compliance must be addressed. Finally, in the evaluation phase, these elements are reviewed again to ensure they have been properly implemented. The Project Manager oversees governance and compliance throughout the entire project lifecycle.
Yes, Generative AI is one type of AI, and other, less advanced AIs also exist. All AI technologies, including Generative AI, will continue to evolve. Tools may improve or change over time.
AI projects might not be completed immediately just like all the projects. New regulations, compliance requirements, and evolving business demands will drive continuous AI projects to achieve results. AI grows and learns from the data used.
The CPMAI Framework is based on CRISP-DM and is essentially a framework built on data management. While it does include a few design thinking concepts, it is not necessarily a framework based on design thinking.
No, CPMAI is not about replacing human project managers. Instead, it equips professionals with a structured methodology to use AI effectively in project management. The goal is to improve human decision-making, efficiency, and outcomes by integrating AI.