“Six Sigma for Small and Mid-Sized Organizations” has been added to your cart. View cart

The Project Management AI Handbook

Name: The Project Management AI Handbook
SKU: 978-1-60427-205-5
Availability: InStock

Retail Price: $59.95

$49.95

Leveraging Generative Tools in Waterfall and Agile Environments
By Dr. Prasad S. Kodukula, PMP, PgMP, DASSM and Guz Vinueza, M.S., MBA
Hardcover, 7×10, 334 pages
ISBN: 978-1-60427-205-5
e-ISBN: 978-1-60427-859-0
August 2025

This book is also available for rent

SKU: 978-1-60427-205-5 Categories: Business, Project and Program Management Books

Description

The Project Management AI Handbook: Leveraging Generative Tools in Waterfall and Agile Environments is an essential guide for project and portfolio management professionals, business leaders, and anyone interested in using generative AI to enhance project management. Packed with use cases and prompts, this book illustrates how AI tools can be applied through real-world case studies that mirror actual projects and portfolios. Whether you are managing projects using waterfall or agile methods, this book demonstrates how generative AI can automate tasks, streamline documentation, generate project plans, forecast risks, and optimize project performance with greater efficiency and accuracy.

Key Features

Comprehensive Use Cases: Illustrates numerous real-world applications of generative AI in both waterfall and agile project environments with specific examples
Prompts for Dozens of Use Cases: Provides detailed prompts for a wide variety of use cases in both portfolio management and project management, covering both waterfall and agile methods
Step-by-Step Guidance: Offers practical, actionable steps on how to integrate AI tools into everyday project management tasks such as planning, reporting, and risk management
Real-World Case Studies: Features case studies that reflect real-world project scenarios, offering insights on how AI can enhance efficiency and decision making
AI-Enhanced Portfolio Management: Demonstrates how AI can optimize portfolio-level tasks such as resource allocation, performance forecasting, and strategic alignment
Primer on Project Management Essentials: Includes foundational chapters on portfolio management and waterfall and agile methods—perfect for readers new to project management
Exclusive Online Repository: Readers gain access to a dedicated website that houses all the prompts and case studies from the book, along with regularly updated content and new additions to enhance their learning experience

About the author(s)

Dr. Prasad Kodukula, PMP, PgMP, DASM, DASSM, BCES, is a PMI Fellow, USA Today best-selling author, thought leader, inventor, and entrepreneur with over 40 years of professional experience. As a global ambassador for project management, Prasad has delivered lectures on project management in nearly 50 countries and has worked with 40 Fortune 100 companies (including Abbott, BP, Caterpillar, Dow, IBM, JPMorgan Chase, Kraft, and United Technologies) across all 11 S&P industrial sectors. Prasad is the CEO and co-founder of two companies: Kodukula & Associates, Inc., a project management coaching and consulting firm, and NeoChloris, Inc., a renewable energy company.

Prasad teaches project management at the University of Chicago and Illinois Tech and is also a LinkedIn Learning Instructor. He has been honored by the Project Management Institute (PMI) three times, receiving the 2020 PMI Fellow Award, the 2016 Eric Jenett Project Management Excellence Award, and the 2010 PMI Distinguished Contribution Award, recognizing him as “Best of the Best in Project Management.” Additionally, one of the companies he co-founded was named the most innovative environmental technology company in Illinois in 2005. He has also received prestigious awards from the U.S. Environmental Protection Agency and the State of Kansas for his leadership in education, training, and environmental improvement. Prasad is a co-author or contributing author of 12 books and over 40 articles, and he holds four patents.

Gustavo “Guz” Vinueza, M.S., MBA, is a seasoned technology and risk consultant with over 20 years of experience spanning various industries. A recognized thought leader, Guz is frequently invited to speak at prominent forums, including PMI, AACE, INFORMS, and SPE. He has delivered thousands of hours of training in quantitative risk management and project management to clients across Latin America, the U.S., and the Middle East, working with organizations such as the U.S. Army Corps of Engineers, Borg Warner, Amway, Ontario Power Generation, and DEWA, among others. His expertise has positioned him as a leader in machine learning, advanced analytics, and decision support systems. In addition to his consulting career, Guz has held academic roles at institutions in Latin America and Spain, where he teaches courses in business analytics, data science, project management, and agile methodologies. Professionally, he has served in key leadership positions, including as Consultant Director at The Ferryfield Group, Data Director at Betterfly, and Director of Consulting at Palisade. Guz holds advanced degrees, including a postgraduate diploma in AI and machine learning from the University of Texas at Austin. As a published author, he contributes to global discussions on AI and data-driven strategies, shaping the future of technology and business.

Chapter 1: Introduction
The Book’s Intent
Why Waterfall and Agile Environments?
Integrating Project Portfolio Management
Practical Applications
Companion Website: pmaihandbook.com
What Is This Book Not About?
How Is This Book Organized?

Chapter 2: Introduction to AI in Project Management
Artificial Intelligence
Definitions of AI
Strong AI and Weak AI
Supervised and Unsupervised Learning
Machine Learning and Deep Learning
Neural Networks
Generative AI
Evolution of AI
Nexus of Project Management and AI
Uses of AI in Project Management
Benefits of AI in Project Management
Potential Use Cases of AI in Project Management
Challenges with Integrating AI into Project Management
Strategic Integration of AI in Project Management
Sustainability and Environmental Considerations
Future Trends
In Conclusion

Chapter 3: Generative AI
Definition and Overview
Evolution of Gen AI
Distinction Between Gen AI and Other AI Technologies
Gen AI
Role of Data in Gen AI Models
New Search vs. Traditional Search
Gen AI Engagement
Ethical Considerations
Commercial Players in Gen AI
In Conclusion

Chapter 4: Generative AI Engagement
What Is GAE?
Principles of GAE
PRIME
Hallucinations
Example of Applying Prime with GAE Principles
Prompt Engineering
Challenges and the Strategies for Overcoming Them in Applying Gen AI to Project Management
In Conclusion

Chapter 5: AI Use Cases for Everyday Project Tasks
1 . Writing Professional Emails
2 . Creating Presentations
3 . Summarizing Reports
4 . Generating Templates
5 . Analyzing Data
In Conclusion

Section 2: AI in Portfolio Management
Chapter 6: Project Portfolio Management Essentials
Definition and Overview
Importance of PPM in Organizational Success
Key Functions of PPM
AI Tools in PPM
PPM Input Data for AI Applications
In Conclusion

Chapter 7: AI Use Cases in Portfolio Management
GeneMatrix Case Study
1 . Strategic Framework
2 . Project Evaluation
3 . Strategic Alignment
4 . Project Categorization
5 . Project Prioritization
6 . Project Selection and Optimization
7 . Efficient Frontier
In Conclusion

Section 3: AI in a Waterfall Environment
Chapter 8: Project Management Essentials
Definitions
Project Management Development Approaches
Waterfall vs. Agile
In Conclusion

Chapter 9: AI Use Cases in Project Initiation
Introducing the Case Study: Project Pinot
1 . Business Case
2 . Project Charter
3 . Stakeholder Registry
4 . Stakeholder Grid
5 . Stakeholder Engagement Assessment Matrix
6 . Communication Plan
In Conclusion

Chapter 10: AI Use Cases in Project Planning
1. Work Breakdown Structure
Estimation
2. Project Scheduling
3. Cost Estimation
4. Resource Allocation and Resource Leveling
5. RACI Chart
6. Integrated Performance Measurement Baseline
7. Risk Register
8. Risk Response Planning
In Conclusion

Chapter 11: AI Use Cases in Project Execution
1. Conflict Resolution
2. Earned Value Management for Cost Performance
3 . Earned Time Management for Schedule Performance
4 . Change Control Form
5 . Project Progress Report
In Conclusion

Chapter 12: AI Use Cases in the Project Closeout Phase
1. Lessons Learned
2. Project Summary Report
In Conclusion

Section 4: AI in an Agile Environment
Chapter 13: Agile Essentials
Introduction to Agile
History and Development of Agile
Scrum
In Conclusion

Chapter 14: AI Use Cases in Agile Scrum Artifacts
Project Victor Case Study
1. Product Backlog: The Hub of Agile Development
2. Epics
3. User Stories
4. Predictive Analytics
In Conclusion

Chapter 15: AI Use Cases in Agile Scrum Ceremonies
Sprint Planning
1. Creating Tasks from User Stories
2. Task Estimation
3. Sprint Backlog
Sprint Reviews
4. Sprint Assessment
5. Burndown and Burnup Charts
6. Velocity Charts
Sprint Retrospectives
7. Retrospectives
In Conclusion

Chapter 16: Final Thoughts—Embracing the Future of Project Management with AI
Key Themes Recap: Reflections on Our Journey with AI in Project Management
Embracing the Future of Project Management with AI
Recommendations: Navigating AI Integration
Confronting the Fear: Will AI Take My Job?
In Conclusion: The Human Spirit at the Helm

References
Index

Reviews

“Practical, insightful, and timely, The Project Management AI Handbook is a must-read for project professionals navigating the intersection of AI and project management. Dr. Prasad Kodukula and Guz Vinueza masterfully bridge the gap between theory and practice, offering actionable tools and real-world examples for both waterfall and agile methodologies. This book is not just a guide—it’s a roadmap for leveraging AI to transform how projects are managed and value is delivered.”
—Antonio Nieto-Rodriguez, Thinkers50, HBR Author, PMI Fellow, CEO

“I could write a book about the profound insights found in this groundbreaking publication! The holistic approach taken keeps the reader eager to turn each page, uncovering not only ‘truths’ about AI but also its transformative and practical applications in project management. This book is a must-read for professionals seeking actionable strategies to integrate AI into their workflows effectively.”
—Lee Lambert, A Founder of the PMP, PMI Fellow, CEO

“This pathfinding book provides project managers with a thorough guide to incorporating AI and ML into project workflows, enhancing risk management, and maximizing efficiency. Whether for the seasoned professional or the novice, this book will equip you to navigate the complexities of modern project management.”
—Dr. Gregory Baecher, G.L. Martin Institute Professor of Engineering, University of
Maryland; Member, National Academy of Engineering