Applying Artificial Intelligence to Project Management

Name: Applying Artificial Intelligence to Project Management | Figurative language in use, constructions and typology
Brand: De Gruyter
Price: 44.95 EUR
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Figurative language in use, constructions and typology

Paul Boudreau(Autor*in)

De Gruyter (Verlag)

1. Auflage

Erschienen am 8. November 2024

220 Seiten

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978-1-5015-1930-7 (ISBN)

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Inhalt

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

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