- Discover why AI projects struggle and why AI project management requires a disciplined, structured methodology.
- Review how iterative delivery supports AI project success when uncertainty, experimentation, and changing data conditions are present.
- Understand how CPMAI helps guide ethical, effective outcomes across AI initiatives.
- Connect AI project management to measurable business value, strategic impact, team alignment, and sustainable adoption.
PMI Certified Professional in Managing AI Training Course
PMI Certified Professional in Managing AI (PMI-CPMAI)™ Training Course
Prepare for the PMI-CPMAI™ certification and build the structure, credibility, and practical playbook to turn AI innovation into ethical, measurable, and lasting business value.
Course focus: AI project management, business alignment, data needs, data preparation, iterative AI development, testing and evaluation, operationalization, governance, ethics, measurable outcomes, and responsible AI delivery.
Course Overview
Build the structure and credibility to manage AI initiatives with strategic impact.
Accumentum’s PMI Certified Professional in Managing AI (PMI-CPMAI)™ Training Course prepares learners to pursue PMI’s AI project management certification and develop the practical framework needed to lead AI initiatives from business need through operational adoption.
PMI describes PMI-CPMAI as a license to lead the future of AI. The certification gives professionals tools to build with AI effectively and provides a playbook to help secure AI success through a tool-agnostic, results-driven approach.
This course is designed for professionals who are already delivering AI initiatives or who are ready to start. PMI identifies relevant audiences including project managers, technologists, data experts, and consultants who need a structured way to turn AI innovation into measurable, lasting business value.
The training follows the PMI-CPMAI Exam Prep Course structure and is organized around the six CPMAI methodology phases. Learners review the need for AI project management, match AI with business needs, identify data requirements, manage data preparation, iterate AI development and delivery, test and evaluate AI systems, and operationalize AI responsibly.
19M+AI jobs projected globally by 2030, as referenced by PMI from the World Economic Forum.
$632BEstimated global AI spend by 2028, as referenced by PMI from IDC Research.
86%Enterprises ranking AI and big data as top-priority skills, as referenced by PMI from Dremio.
Course Objectives
Prepare to lead AI projects from vision to measurable, responsible outcomes.
01
Translate AI Vision
Turn bold AI visions into clear, achievable project plans that connect innovation with business need, scope, feasibility, and return on investment.
02
Manage AI Complexity
Navigate fast-changing technologies without depending on tool-specific training by applying a structured, tool-agnostic AI project methodology.
03
Align Diverse Teams
Unite cross-functional teams around a shared process that supports project clarity, technical collaboration, business alignment, and AI delivery discipline.
04
Deliver Responsible Outcomes
Deliver AI outcomes that are ethical, measurable, explainable, reliable, and built to withstand business scrutiny.
Who Should Attend
- Project managers who want to adapt project management knowledge for AI, advanced data, automation, machine learning, and generative AI initiatives.
- Technologists who need a structured process for aligning AI solutions, data needs, model development, evaluation, and operational adoption.
- Data experts who support AI project scoping, data readiness, data preparation, compliance, model testing, monitoring, and lifecycle management.
- Consultants and solution providers who need a comprehensive approach to managing, scoping, evaluating, and delivering AI projects successfully.
Eligibility and Recommended Readiness
- PMI lists PMI-CPMAI as having no experience required, making it accessible to professionals already delivering AI initiatives and those eager to start.
- The course is designed for learners who want structure and credibility to turn AI innovation into measurable, lasting value.
- Learners should be prepared to study business alignment, feasibility, scope, ROI, data requirements, compliance, data preparation, model development, testing, evaluation, operationalization, governance, and continuous improvement.
- The PMI-CPMAI Exam Prep Course includes 21 hours of learning and can earn 21 PDUs toward maintenance of other PMI certifications.
Pathway Map
The PMI-CPMAI training course follows the complete AI project management pathway.
The curriculum connects PMI’s AI project management certification structure with the CPMAI methodology phases, including business alignment, data needs, data preparation, AI development and delivery, testing and evaluation, operationalization, governance, ethics, and continuous improvement.
1
The Need for AI Project Management
2
Matching AI with Business Needs
3
Identifying Data Needs for AI Projects
4
Managing Data Preparation Needs
5
Iterating Development and Delivery
6
Testing and Evaluating AI Systems
7
Operationalizing AI Responsibly
8
Certification Steps and Exam Day
9
PDUs and Certification Maintenance
10
PMI-CPMAI Exam Readiness
Course Content
Full PMI-CPMAI curriculum breakout.
- Align AI solutions and strategy to real business needs before moving into development or tool selection.
- Assess feasibility, define return on investment, and establish clear project scope for AI initiatives.
- Translate AI vision into achievable project plans that can withstand business scrutiny.
- Practice using a shared process to unite cross-functional teams around business alignment, project clarity, and measurable outcomes.
- Select the right data to support AI project goals and anticipated solution outcomes.
- Review compliance considerations that shape AI data sourcing, usage, controls, and lifecycle management.
- Build the infrastructure foundation needed to support AI data management across the project lifecycle.
- Connect data needs to business value, project feasibility, model development, and AI system reliability.
- Transform raw data into AI-ready inputs through structured preparation activities.
- Review quality checks, data augmentation, and compliance controls that support effective AI development.
- Understand how data preparation affects model performance, explainability, reliability, and business confidence.
- Apply data preparation thinking to AI project planning, delivery, evaluation, and governance.
- Build and validate AI models through iterative development and delivery cycles.
- Review how machine learning and generative AI project work benefits from incremental development, validation, and feedback.
- Understand how AI delivery differs from traditional project delivery when experimentation, data readiness, and model behavior evolve.
- Connect iterative delivery to ethical, effective outcomes and measurable AI project success.
- Test and monitor AI models to determine whether results are reliable, explainable, and aligned with project goals.
- Review model drift and why AI systems require ongoing evaluation beyond initial deployment readiness.
- Understand how testing and evaluation support ethical outcomes, business scrutiny, stakeholder confidence, and operational trust.
- Apply testing and evaluation concepts to AI lifecycle management, governance, and continuous improvement.
- Operationalize AI responsibly by preparing AI systems for use, adoption, oversight, and continued value delivery.
- Review governance practices that help AI solutions remain aligned with goals, controls, policies, and business expectations.
- Plan for continuous improvement as AI technologies, data conditions, model outputs, and organizational requirements change.
- Connect operationalization to strategic impact, enterprise adoption, ethical practice, measurable value, and long-term success.
- Review PMI’s stated steps to PMI-CPMAI certification: check eligibility, confirm your details, schedule, study, and earn.
- Understand the PMI-CPMAI exam format, including 120 questions and 160 minutes of exam time.
- Review PMI-CPMAI availability in Arabic, Brazilian Portuguese, Chinese Simplified, Chinese Traditional, English, French, German, Japanese, Korean, and Spanish LATAM.
- Connect the certification process to exam preparation, study planning, certification readiness, and professional AI project management credibility.
- Earn 21 PDUs toward maintenance of other PMI certifications while completing the PMI-CPMAI Exam Prep Course.
- Review PMI’s PDU allocation for the course: 7 PDUs in Business Acumen, 11 PDUs in Ways of Working, and 3 PDUs in Power Skills.
- Understand PMI-CPMAI maintenance expectations, including 30 PDUs every 3 years.
- Connect ongoing learning to keeping AI project management skills sharp, relevant, and aligned to a constantly evolving field.
- Review the complete PMI-CPMAI Exam Prep Course structure across AI project management need, business matching, data needs, data preparation, development, testing, and operationalization.
- Use scenario-based exercises, case studies, guided Exam Content Outline references, and independent study activities to reinforce understanding.
- Prepare for the PMI-CPMAI exam by connecting methodology phases to ethical, measurable, reliable, and explainable AI project outcomes.
- Build confidence in using a tool-agnostic, results-driven AI project management approach that supports strategic impact and responsible AI success.
Course Features
Designed for PMI-CPMAI exam preparation and practical AI project management capability.
Scenario-Based Exercises
Apply AI project management concepts through scenario-based learning that supports immediate use across real AI project environments.
Case Study Application
Use case studies to connect AI strategy, business needs, data readiness, model development, testing, and operational adoption.
Workbook-Guided Learning
Reinforce core concepts through structured workbook activities aligned to the CPMAI methodology and PMI-CPMAI exam preparation.
Exam Content Review
Review Exam Content Outline references and independent study activities to build a strong understanding of the PMI-CPMAI material.
Certification Exam
Prepare for the official PMI Certified Professional in Managing AI certification exam.
PMI-CPMAI Exam Readiness
Accumentum’s PMI-CPMAI Training Course prepares learners to pursue certification readiness across the complete AI project management lifecycle.
Upon completing the PMI Certified Professional in Managing AI (PMI-CPMAI)™ Training Course with Accumentum, learners will be prepared to pursue the official PMI-CPMAI certification exam and validate their ability to manage AI project complexity with strategic impact.
PMI lists the PMI-CPMAI exam as 120 questions with an exam time of 160 minutes. PMI also describes the certification as tool-agnostic and results-driven, confirming that certified professionals can manage complexity, align diverse teams, and create AI solutions that combine technical excellence with strategic impact.
The 21-hour PMI-CPMAI Exam Prep Course provides the knowledge and skills to pass the exam and manage AI projects effectively. It is organized around the six CPMAI methodology phases and uses scenario-based exercises, case studies, a downloadable workbook, multimedia content, guided Exam Content Outline references, and independent study activities.
The course and certification exam are available in Arabic, Brazilian Portuguese, Chinese Simplified, Chinese Traditional, English, French, German, Japanese, Korean, and Spanish LATAM.
Frequently Asked Questions
Understand how Accumentum’s PMI-CPMAI Training Course supports AI project management certification preparation, CPMAI methodology learning, exam readiness, PDUs, and certification maintenance.
PMI Certified Professional in Managing AI (PMI-CPMAI)™ is PMI’s AI project management certification. PMI describes it as a tool-agnostic, results-driven certification that confirms the ability to manage complexity, align diverse teams, and create AI solutions with strategic impact.
PMI identifies project managers, technologists, data experts, and consultants as professionals who can benefit from PMI-CPMAI, whether they are already delivering AI initiatives or eager to start.
PMI lists PMI-CPMAI as having no experience required. The certification is positioned for professionals already delivering AI initiatives and for professionals who are ready to begin building AI project management capability.
The PMI-CPMAI exam includes 120 questions.
PMI lists the PMI-CPMAI exam time as 160 minutes.
The PMI-CPMAI Exam Prep Course is 21 hours and provides the knowledge and skills to pass the exam and manage AI projects effectively.
The six CPMAI methodology phases covered by PMI’s course include matching AI with business needs, identifying data needs, managing data preparation needs, iterating development and delivery, testing and evaluating AI systems, and operationalizing AI.
The PMI-CPMAI Exam Prep Course provides 21 PDUs toward maintenance of other PMI certifications: 7 PDUs in Business Acumen, 11 PDUs in Ways of Working, and 3 PDUs in Power Skills.
PMI-CPMAI holders must earn 30 professional development units every 3 years. PMI lists qualifying PDU activities including learning, teaching others, presenting, reading, volunteering, and creating content.
PMI lists the course and certification exam as available in Arabic, Brazilian Portuguese, Chinese Simplified, Chinese Traditional, English, French, German, Japanese, Korean, and Spanish LATAM.
Enrollment
Enroll in the PMI Certified Professional in Managing AI Training Course with Accumentum.
Enroll in Accumentum’s PMI Certified Professional in Managing AI (PMI-CPMAI)™ Training Course to prepare for the PMI-CPMAI certification exam and strengthen your ability to manage AI initiatives through a structured, responsible, and results-driven methodology.
You will study the need for AI project management, matching AI with business needs, identifying data needs, managing data preparation, iterating development and delivery, testing and evaluating AI systems, and operationalizing AI responsibly.
This course is ideal for project managers, technologists, data experts, consultants, and professionals who want the structure and credibility to turn AI innovation into measurable, lasting business value. For detailed information, upcoming course dates, cohort availability, and enrollment support, visit Accumentum’s registration page linked below.
Build AI project management capability with PMI-CPMAI training.
Prepare for the PMI-CPMAI certification exam while building practical capability across AI strategy, business alignment, data needs, data preparation, iterative development, testing, evaluation, governance, operationalization, ethics, measurable outcomes, and continuous improvement.