The Project Management AI Handbook

• 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

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

“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