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

Enabling project managers to adapt to the new technology of artificial intelligence, this first comprehensive book on the topic discusses how AI will reinvent the project world and allow project managers to focus on people. Studies show that by 2030, 80 percent of project management tasks, such as data collection, reporting, and predictive analysis, will be carried out by AI in a consistent and efficient manner. This book sets out to explore what this will mean for project managers around the world and equips them to embrace this technological advantage for greater project success. Filled with insights and examples from tech providers and project experts, this book is an invaluable resource for PMO leaders, change executives, project managers, programme managers, and portfolio managers. Anyone who is part of the global community of change and project leadership needs to accept and understand the fast- approaching AI technology, and this book shows how to use it to their advantage.

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.

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

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.

Data Analytics in Project Management. Data analytics plays a crucial role in business analytics. Without a rigid approach to analyzing data, there is no way to glean insights from it. Business analytics ensures the expected value of change while that change is implemented by projects in the business environment. Due to the significant increase in the number of projects and the amount of data associated with them, it is crucial to understand the areas in which data analytics can be applied in project management. This book addresses data analytics in relation to key areas, approaches, and methods in project management. It examines: • Risk management • The role of the project management office (PMO) • Planning and resource management • Project portfolio management • Earned value method (EVM) • Big Data • Software support • Data mining • Decision-making • Agile project management Data analytics in project management is of increasing importance and extremely challenging. There is rapid multiplication of data volumes, and, at the same time, the structure of the data is more complex. Digging through exabytes and zettabytes of data is a technological challenge in and of itself. How project management creates value through data analytics is crucial. Data Analytics in Project Management addresses the most common issues of applying data analytics in project management. The book supports theory with numerous examples and case studies and is a resource for academics and practitioners alike. It is a thought-provoking examination of data analytics applications that is valuable for projects today and those in the future.

The goal of the new edition is to continue with a systems view of the world. For a more robust and worldwide market dissemination, the new edition has changed to a reference book. The project systems approach to project management, is needed in executing projects across countries and across cultures, which is a crucial requirement in today's globalized and intertwined economics. The book uses ample graphical representations to clarify the concepts and techniques presented. The case examples help to reinforce the topics covered. Several illustrative examples and practice exercises are included. Each chapter is updated and new chapters include Project Simulation and Project Templates. A new chapter on managing complex projects in an age of artificial intelligence adds a unique value to the book. Features Highlights contemporary best practices of project management Uses a systems framework to integrate quantitative and qualitative tools Offers illustrative examples and practice exercises Covers project schedule performance appraisal techniques Discusses the knowledge areas contained in the Project Management Book of Knowledge (PMBOK) Presents software applications for project management, as well as case examples

Strategic change occurs through the successful execution of projects. This is much easier said than done! There are hundreds of references covering the concepts underlying project management. But since each project is unique, project managers frequently learn more through the school of hard knocks than they do from theory. Whether you are new to the field or a senior practitioner, the lessons in this book will provide you with pragmatic, practice-based insights into project leadership.

Data Science and its applications