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.

Course Content

Full PMI-CPMAI curriculum breakout.

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.

PMI Certified Professional in Managing AI Certification Badge

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.

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.