Chapter 9: Generative AI and Large Language Models

Chapters in this book

1. Frontmatter i
2. Contents v
3. Preface xi
4. Acknowledgments xv
5. About the Author xvii
6. Part I: Fundamental Concepts of AI in Project Management
7. Chapter 1: Why Project Management Needs AI 1
8. Chapter 2: Two AI Components for Projects 11
9. Chapter 3: The Business Case for AI 21
10. Chapter 4: Automating Project Management Tasks 27
11. Part II: The Importance of Data
12. Chapter 5: Providing Good Project Data 33
13. Chapter 6: Acquiring and Using Data 45
14. Part III: AI Solutions for Project Problems
15. Chapter 7: Predicting Project Results Using Machine Learning Algorithms and Supervised Learning to Predict Results 57
16. Chapter 8: Improving Project Productivity with NLP 89
17. Chapter 9: Generative AI and Large Language Models 111
18. Chapter 10: Genetic Algorithms for Project Navigation 119
19. Part IV: Applying AI to Project Processes
20. Chapter 11: Project Initiation, Planning, Delivery, and Close 127
21. Chapter 12: Project Control and Project Termination 139
22. Chapter 13: AI for Agile Process Effectiveness 145
23. Chapter 14: Applying AI to Resolve Project Failure 149
24. Part V: Acquiring AI Solutions
25. Chapter 15: The Build or Buy Decision 157
26. Chapter 16: Evaluating and Acquiring AI Software 165
27. Chapter 17: Implementing AI Solutions 173
28. Part VI: Adapting to AI in Project Management
29. Chapter 18: Changes to Roles of the Project Manager, PMO, and Project Team 181
30. Chapter 19: Ethical Implications of AI in Project Management 195
31. Chapter 20: The Rapid Advance of AI Technology 205
32. Chapter 21: Conclusion 211
33. Appendix: Terms and Definitions 213
34. Index 217