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Applying Artificial Intelligence to Project Management

Frontmatter

Contents

Preface

Acknowledgments

About the Author

Chapter 1: Why Project Management Needs AI

Chapter 2: Two AI Components for Projects

Chapter 3: The Business Case for AI

Chapter 4: Automating Project Management Tasks

Chapter 5: Providing Good Project Data

Chapter 6: Acquiring and Using Data

Chapter 7: Predicting Project Results Using Machine Learning Algorithms and Supervised Learning to Predict Results

Chapter 8: Improving Project Productivity with NLP

Chapter 9: Generative AI and Large Language Models

Chapter 10: Genetic Algorithms for Project Navigation

Chapter 11: Project Initiation, Planning, Delivery, and Close

Chapter 12: Project Control and Project Termination

Chapter 13: AI for Agile Process Effectiveness

Chapter 14: Applying AI to Resolve Project Failure

Chapter 15: The Build or Buy Decision

Chapter 16: Evaluating and Acquiring AI Software

Chapter 17: Implementing AI Solutions

Chapter 18: Changes to Roles of the Project Manager, PMO, and Project Team

Chapter 19: Ethical Implications of AI in Project Management

Chapter 20: The Rapid Advance of AI Technology

Chapter 21: Conclusion

Appendix: Terms and Definitions

Index

Boudreau, Paul

This book describes the AI tools in concept and how they apply directly to project success. It also demonstrates the strategy and methods used to purchase and implement AI tools for project management. You will understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using artificial intelligence for project management improves project success rates.

This book describes the AI tools in concept and how they apply directly to project success. It also demonstrates the strategy and methods used to purchase and...

Format

Applying Artificial Intelligence to Project Management

Paul Boudreau

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