3 books on AI for Project Management [PDF]
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These books are covering various aspects of AI's role in automating project workflows, enhancing team collaboration and improving decision-making.
1. Project Management with AI For Dummies
2025 by Daniel Stanton
The main insight of this book for dummies is that AI, that have read all the books on project management in the world, of course knows all the best practices, all the pitfalls and all the tasks of a project manager. And as in any other field, if you at least have the competence to ask the right question (like What risks do you see for increasing the time frame of this project? or How should I distribute tasks between employees in this project?) - AI will give you an answer that looks like the truth and your task will be to control and correct it. However, the main secret is how to transfer all the project data into the context of AI. The answer is - only project management systems with built-in integration with language models can do this. And at the end of this book, ten of the most popular systems that have such integration are listed.
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2. Tomorrow's Data Empowered Project Management: Agile Decision Making, Sustainability and AI
2025 by Öncü Hazır, Maria Elena Bruni
This book explains how AI and big data are being used for project management today. The author acknowledges that the use of these tools in project management remains very limited. This can be partly explained by the unique nature of projects, that differ from activities and processes that are repetitive or well-known. Unlike ongoing operations, projects are temporary initiatives with specific deadlines. Projects may involve different teams, stakeholders and resources in a dynamic environment, which features variability not found in routine operations. This nature of projects makes the application of standard big data analytics methods quite challenging. Each stage of project management – planning, execution, monitoring and completion – requires continuous decision making. But as we know, big data analytics tools are used to support decision making. For example, data visualization tools enhance project managers’ perception of the big picture by using cognitive mechanisms. They provide understandable graphical representations, including tables and graphs, to summarize complex large data sets, facilitating meaning and analysis for informed decision making.
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3. Innovation Project Management: Methods, Case Studies, and Tools for Managing Innovation Projects
2022 by Harold Kerzner
The author of this book asks himself whether AI could imitate the cognitive functions of a project manager, such as situation analysis and decision making. And is it possible to describe the mind of a project manager so accurately that it could be simulated using AI algorithms? If so, the author believes that there could be several applications of AI in project management: monitoring project constraints, predicting critical situations, selecting the most profitable projects for a project portfolio and optimizing schedules. Project managers are often forced to make quick decisions based on intuition rather than step-by-step analysis by computers. Nothing is completely true or false, since assumptions must be made. The more information we have, the fewer such assumptions we have. Based on big data, AI can reason and solve problems even with incomplete information, model the future and offer solutions that maximize the value of decisions. So, for AI to be useful in project management, it is necessary to combine disparate knowledge into an enterprise knowledge management system. The more information is available to AI, the higher is its value. So the first step should be to consolidate project management intellectual property and make it accessible to AI tools.
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Project Management with AI For Dummies
2025 by Daniel Stanton
The main insight of this book for dummies is that AI, that have read all the books on project management in the world, of course knows all the best practices, all the pitfalls and all the tasks of a project manager. And as in any other field, if you at least have the competence to ask the right question (like What risks do you see for increasing the time frame of this project? or How should I distribute tasks between employees in this project?) - AI will give you an answer that looks like the truth and your task will be to control and correct it. However, the main secret is how to transfer all the project data into the context of AI. The answer is - only project management systems with built-in integration with language models can do this. And at the end of this book, ten of the most popular systems that have such integration are listed.
Download PDF
2. Tomorrow's Data Empowered Project Management: Agile Decision Making, Sustainability and AI
2025 by Öncü Hazır, Maria Elena Bruni
This book explains how AI and big data are being used for project management today. The author acknowledges that the use of these tools in project management remains very limited. This can be partly explained by the unique nature of projects, that differ from activities and processes that are repetitive or well-known. Unlike ongoing operations, projects are temporary initiatives with specific deadlines. Projects may involve different teams, stakeholders and resources in a dynamic environment, which features variability not found in routine operations. This nature of projects makes the application of standard big data analytics methods quite challenging. Each stage of project management – planning, execution, monitoring and completion – requires continuous decision making. But as we know, big data analytics tools are used to support decision making. For example, data visualization tools enhance project managers’ perception of the big picture by using cognitive mechanisms. They provide understandable graphical representations, including tables and graphs, to summarize complex large data sets, facilitating meaning and analysis for informed decision making.
Download PDF
3. Innovation Project Management: Methods, Case Studies, and Tools for Managing Innovation Projects
2022 by Harold Kerzner
The author of this book asks himself whether AI could imitate the cognitive functions of a project manager, such as situation analysis and decision making. And is it possible to describe the mind of a project manager so accurately that it could be simulated using AI algorithms? If so, the author believes that there could be several applications of AI in project management: monitoring project constraints, predicting critical situations, selecting the most profitable projects for a project portfolio and optimizing schedules. Project managers are often forced to make quick decisions based on intuition rather than step-by-step analysis by computers. Nothing is completely true or false, since assumptions must be made. The more information we have, the fewer such assumptions we have. Based on big data, AI can reason and solve problems even with incomplete information, model the future and offer solutions that maximize the value of decisions. So, for AI to be useful in project management, it is necessary to combine disparate knowledge into an enterprise knowledge management system. The more information is available to AI, the higher is its value. So the first step should be to consolidate project management intellectual property and make it accessible to AI tools.
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
