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Applying Artificial Intelligence to Project Management
Author Paul Boudreau shares the keys to project management success using a modern artificial intelligence. Within the pages of Applying Artificial Intelligence to Project Management, Boudreau describes five AI tools in concept and how they apply directly to project success, as well as the strategy and method to use to purchase and implement AI tools for project management. 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. Read project management success stories in one of the best business books on machine learning, and prepare to leave behind that 50 percent project success rate for one that’s 95 percent or higher.
- GenresBusiness
183 pages, Paperback
Published November 13, 2019
55 people are currently reading
80 people want to read
About the author
Paul Boudreau
11 books3 followersPaul is a highly respected project management professional with over thirty-five years experience in the technology industry. His extensive project management work includes successful project implementations in Canada, the United States, and the United Kingdom. Paul is a professor at Algonquin College in Ottawa where he is currently using his in-depth knowledge of project management and a background in software to research and develop AI concepts. He is known for presenting compelling arguments as to why AI technology will become essential to the way we manage projects.
Paul is available to deliver presentations on the topic of AI or join discussion groups.
Paul is available to deliver presentations on the topic of AI or join discussion groups.
Ratings & Reviews
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Displaying 1 - 4 of 4 reviews
July 3, 2023
Esperaba una información más desarrollada, hay mucho preámbulo, pero obtuve la información necesaria un tanto acotada.
February 27, 2025
Applying AI to Project Management is an insightful but somewhat limited exploration of how artificial intelligence can enhance project management. The book attempts to map AI capabilities onto traditional project management functions, outlining where AI could be useful in automating tasks, improving decision-making, and boosting efficiency. However, while the concepts are well explained, the book lacks real-world practical application, especially for those looking for immediate ways to implement AI in their projects.
One of the key limitations is that much of the AI integration described requires company-specific data to be truly effective. Without access to internal datasets, many of the AI applications remain theoretical unless generative AI is leveraged with carefully crafted prompts. This makes some of the proposed AI uses feel more aspirational than actionable, especially for project managers looking for tangible ways to integrate AI into their workflows today.
That being said, there are some useful takeaways. The discussion on generative AI’s role in productivity—such as automating reports, assisting with stakeholder communication, and helping with risk assessments—is practical and relevant. The most intriguing idea is the concept of a digital twin that simulates project decisions, allowing managers to test different scenarios before committing to a course of action. While not revolutionary, it is an interesting way to think about predictive analytics in project management.
Overall, the book provides a good high-level overview of AI’s potential in project management, but it doesn’t break new ground or provide radically new insights. It’s best suited for those who are new to the intersection of AI and project management or want to explore the possibilities, but for those already familiar with AI’s role in productivity and decision-making, there’s little here that feels genuinely transformative.
One of the key limitations is that much of the AI integration described requires company-specific data to be truly effective. Without access to internal datasets, many of the AI applications remain theoretical unless generative AI is leveraged with carefully crafted prompts. This makes some of the proposed AI uses feel more aspirational than actionable, especially for project managers looking for tangible ways to integrate AI into their workflows today.
That being said, there are some useful takeaways. The discussion on generative AI’s role in productivity—such as automating reports, assisting with stakeholder communication, and helping with risk assessments—is practical and relevant. The most intriguing idea is the concept of a digital twin that simulates project decisions, allowing managers to test different scenarios before committing to a course of action. While not revolutionary, it is an interesting way to think about predictive analytics in project management.
Overall, the book provides a good high-level overview of AI’s potential in project management, but it doesn’t break new ground or provide radically new insights. It’s best suited for those who are new to the intersection of AI and project management or want to explore the possibilities, but for those already familiar with AI’s role in productivity and decision-making, there’s little here that feels genuinely transformative.
May 29, 2024
A well written book but it’s very much a ‘how too’ I think I was after something a bit more innovative. It talks about basic project management principles and overlays AI, useful but not radical.
June 17, 2024
Misnamed. Very little in the way of immediate right now application.
Displaying 1 - 4 of 4 reviews