Ai Driven Decision Making Examples
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AI-Driven Leadership: Transformative Strategies for Navigating the Age of Automation
In this groundbreaking book, readers will embark on an insightful journey into the transformative power of AI for leadership. The author masterfully weaves together cutting-edge insights into AI capabilities with practical strategies, empowering leaders to navigate the age of automation with confidence and vision. Throughout the pages, readers will discover how AI can augment their leadership abilities, enabling them to make informed decisions, improve operational efficiency, and enhance employee engagement. The book explores the latest AI technologies and their potential to streamline processes, predict outcomes, and provide real-time insights. It also delves into the ethical considerations and challenges associated with AI adoption, guiding leaders towards a responsible and effective implementation. By integrating AI into their leadership practices, leaders can gain a competitive advantage, foster innovation, and drive organizational growth. This book provides a comprehensive roadmap for leaders seeking to embrace AI and leverage its transformative power to elevate their organizations to new heights. It is an essential guide for anyone seeking to stay ahead in the rapidly evolving landscape of business and technology.
Using Traditional Design Methods to Enhance AI-Driven Decision Making
In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.
Intelligent Decision Making: An AI-Based Approach
Author: Gloria Phillips-Wren
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-03-04
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.