Applying Artificial Intelligence to Project Management
Figurative language in use, constructions and typology
1st Edition
Published on 8. November 2024
220 pages
978-1-5015-1930-7 (ISBN)
Description
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. The book features project management success stories and demonstrates how to leave behind that low project success rate for one that is 95 percent or higher. Supplemental teaching materials are available for use as a textbook.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
US School Grade: College Graduate Student
File size
8,47 MB
ISBN-13
978-1-5015-1930-7 (9781501519307)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Paul Boudreau
Applying Artificial Intelligence to Project Management
Book
11/2024
1st Edition
De Gruyter
€44.95
Article not available at the moment
Person
Paul Boudreau is an instructor of various project management courses, and a project management influencer focused on improving project success by applying artificial intelligence technology. He is recognized by his peers as an expert in the field and has collaborated on several new AI software applications for project management.
Content
- Cover
- Half Title
- Title
- Copyright
- Contents
- Preface
- Acknowledgments
- About the Author
- Part I: Fundamental Concepts of AI in Project Management
- Chapter 1: Why Project Management Needs AI
- Questions
- References
- Chapter 2: Two AI Components for Projects
- Machine Learning
- Natural Language Processing (NLP)
- AI Background
- Software Concepts
- Criticisms of Artificial Intelligence
- Questions
- References
- Chapter 3: The Business Case for AI
- Misunderstandings of AI
- Questions
- References
- Chapter 4: Automating Project Management Tasks
- Questions
- References
- Part II: The Importance of Data
- Chapter 5: Providing Good Project Data
- Managing Poor Data Quality ("Garbage In")
- Data Volume
- Data Significance
- Questions
- References
- Case Study: Insufficient Data
- Chapter 6: Acquiring and Using Data
- Data Mining
- How to Prepare the Data
- Data Management Terms and Actions
- Questions
- References
- Part III: AI Solutions for Project Problems
- Chapter 7: Predicting Project Results Using Machine Learning Algorithms and Supervised Learning to Predict Results
- Example: Prediction Software
- Project Screening and Selection
- Predictions During Project Execution
- Using Prediction Software in a Gating Process
- An Example of Developing Prediction Software
- Building AI Prediction Software for Project Management
- Input
- Processing
- Output
- The Future of Project Prediction Software
- Unsupervised Learning for Clustering Project Issues
- Reinforcement Learning for Improved Decision-Making
- Examples of Machine Learning Solutions
- Building AI Stakeholder Management Software
- Inputs
- Processing
- Output
- Resolving Project Issues Successfully
- Historical Data
- Building AI Issues Management Software
- Inputs
- Processing
- Output
- The Future of Managing Project Issues
- AI Change Control Predictions
- Historical Data
- Managing Change
- Building AI Software for Change Control
- Inputs
- Process
- Output
- The Future of Change Control Software
- Questions
- References
- Chapter 8: Improving Project Productivity with NLP
- Fundamentals of NLP
- Document Analysis
- Sentiment Analysis
- Stakeholder Management Using Sentiment Analysis
- The Pros and Cons of Sentiment Analysis
- Improving Project Team Communication
- A Possible Scenario for Sentiment Analysis During a Project
- Personality and Bias
- Virtual Assistants
- Historical Data and the Virtual Assistant
- Inputs
- Processing
- Output
- The Project Assistant
- The Future of Virtual Assistants for Project Management
- Questions
- References
- Chapter 9: Generative AI and Large Language Models
- Questions
- Chapter 10: Genetic Algorithms for Project Navigation
- Feature Selection
- Selection Optimization
- Optimization Solutions
- The Value of Genetic Algorithms
- A Final Thought on Genetics
- Questions
- References
- Part IV: Applying AI to Project Processes
- Chapter 11: Project Initiation, Planning, Delivery, and Close
- Project Initiation
- Project Planning
- Project Delivery
- Project Close
- Questions
- Case Study: Proactively Managing Large Infrastructure Projects
- Chapter 12: Project Control and Project Termination
- Project Termination
- Questions
- Case Study: Predicting Success and Failure
- Chapter 13: AI for Agile Process Effectiveness
- Questions
- References
- Case Study: Resource Allocation Across a Portfolio
- Chapter 14: Applying AI to Resolve Project Failure
- Questions
- References
- Case Study: Deploying a Mass Transit System
- Part V: Acquiring AI Solutions
- Chapter 15: The Build or Buy Decision
- Resources to Create AI Software for Project Management
- Questions
- Chapter 16: Evaluating and Acquiring AI Software
- Strategy for Implementing AI
- Questions
- References
- Case Study: Vendor Selection
- Chapter 17: Implementing AI Solutions
- The AI Roadmap
- Questions
- Case Study: Deployment Issues
- Part VI: Adapting to AI in Project Management
- Chapter 18: Changes to Roles of the Project Manager, PMO, and Project Team
- Project Managers
- The Project Management Office
- Project Team
- Training
- Questions
- References
- Chapter 19: Ethical Implications of AI in Project Management
- Areas of Ethical Concern
- Data
- Software Development
- Explainable AI
- Inherent Problems in AI Development
- Overcoming the Fear of AI
- Questions
- References
- Chapter 20: The Rapid Advance of AI Technology
- Questions
- References
- Case Study: The Olympic Stadium
- Chapter 21: Conclusion
- Appendix: Terms and Definitions
- Common Abbreviations
- Definitions
- Index
