Author Paul Boudreau shares the keys to project management success using a modern approach: 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.

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. FEATURES: Covers a practical approach to using AI in project management Features a chapter on combining AI with other technologies such as IoT, Blockchain, and virtual reality for further insights into leading-edge changes for project management Demonstrates how to achieve higher productivity and incredible project performance by applying AI concepts Includes supplemental teaching materials for use as a textbook

Artificial Intelligence is finally making its way into project management and the challenge is to take advantage of all the benefits and avoid the pitfalls. In a highly competitive industrial environment, the PMO is in an ideal position to understand, adopt and optimize AI tools for project management. The PMO can align corporate objectives to the new technology and vastly improve the bottom line.This is a both a practical guide and visionary description of how AI will disrupt project management and how the PMO can harness this capability to create a substantial competitive advantage for the organization.

A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human.

The topic of this book is known as dynamic scheduling, and is used to refer to three dimensions of project management and scheduling: the construction of a baseline schedule and the analysis of a project schedule’s risk as preparation of the project control phase during project progress. This dynamic scheduling point of view implicitly assumes that the usability of a project’s baseline schedule is rather limited and only acts as a point of reference in the project life cycle. Consequently, a project schedule should especially be considered as nothing more than a predictive model that can be used for resource efficiency calculations, time and cost risk analyses, project tracking and performance measurement, and so on. In this book, the three dimensions of dynamic scheduling are highlighted in detail and are based on and inspired by a combination of academic research studies at Ghent University (www.ugent.be), in-company trainings at Vlerick Business School (www.vlerick.com) and consultancy projects at OR-AS (www.or-as.be). First, the construction of a project baseline schedule is a central theme throughout the various chapters of the book, and is discussed from a complexity point of view with and without the presence of project resources. Second, the creation of an awareness of the weak parts in a baseline schedule is discussed at the end of the two baseline scheduling parts as schedule risk analysis techniques that can be applied on top of the baseline schedule. Third, the baseline schedule and its risk analyses can be used as guidelines during the project control step where actual deviations can be corrected within the margins of the project’s time and cost reserves. The second edition of this book has seen corrections, additions and amendments in detail throughout the book. Moreover Chapter 15 on "Dynamic Scheduling with ProTrack" has been completely rewritten and extended with a section on "ProTrack as a research tool".

This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.

Understand how to adopt and implement AI in your organization Key Features _ 7 Principles of an AI Journey _ The TUSCANE Approach to Become Data Ready _ The FAB-4 Model to Choose the Right AI Solution _ Major AI Techniques & their Applications: - CART & Ensemble Learning - Clustering, Association Rules & Search - Reinforcement Learning - Natural Language Processing - Image Recognition Description Most AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career. The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations. By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity. What will you learn _ Understand the major AI techniques & how they are used in business. _ Determine which AI technique(s) can solve your business problem. _ Decide whether to build or buy an AI solution. _ Estimate the financial value of an AI solution or company. _ Frame a robust policy to guide the responsible use of AI. Who this book is for This book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers. Table of Contents 1.Preface 2.Acknowledgement 3.About the Author 4.Section 1: Beginning an AI Journey a. AI Fundamentals b. 7 Principles of an AI Journey c. Getting Ready to Use AI 5.Section 2: Choosing the Right AI Techniques a. Inside the AI Laboratory b. How AI Predicts Values & Categories c. How AI Understands and Predicts Behaviors & Scenarios d. How AI Communicates & Learns from Mistakes e. How AI Starts to Think Like Humans 6.Section 3: Using AI Successfully & Responsibly a. AI Adoption & Valuation b. AI Strategy, Policy & Risk Management 7.Epilogue