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Ai-Driven Knowledge Management Assets, Volume 1 - by Meir Russ & Miltiadis Lytras (Hardcover)

Ai-Driven Knowledge Management Assets, Volume 1 - by  Meir Russ & Miltiadis Lytras (Hardcover) - 1 of 1
$115.00 when purchased online
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About this item

Highlights

  • With Artificial Intelligence (AI) reshaping how businesses operate, the integration of intelligent technologies into Knowledge Management (KM) processes offers new opportunities for optimizing data-driven decision-making and enhancing organizational performance.
  • About the Author: Meir Russ is a Professor Emeritus in Management at the Austin E. Cofrin School of Business at the University of Wisconsin-Green Bay, USA, a Research Fellow at the Stellenbosch University in South Africa and a Visiting Professor at the University of Lódź, Poland.
  • 400 Pages
  • Business + Money Management, Knowledge Capital

Description



About the Book



AI-Driven Knowledge Management Assets, Volumes 1 and 2 explore Knowledge Management as a critical element of business strategy and managerial practice, especially in an era of rapid Artificial Intelligence adoption.



Book Synopsis



With Artificial Intelligence (AI) reshaping how businesses operate, the integration of intelligent technologies into Knowledge Management (KM) processes offers new opportunities for optimizing data-driven decision-making and enhancing organizational performance.

AI-Driven Knowledge Management Assets, Volumes 1 and 2 explore KM as a critical element of business strategy and managerial practice, especially in an era of rapid AI adoption. Authors examine KM's foundational and advanced aspects through a managerial lens, highlighting how AI is reshaping contemporary KM practices, and delve into traditional KM strategies and cutting-edge AI applications. Each chapter is enriched with case studies and empirical research that showcase the real-world benefits and challenges of integrating AI into KM. From uncovering the theoretical underpinnings of KM to examining AI-driven innovations that create competitive advantages, this work offers actionable insights and perspectives on future developments. Authors address ethical, sustainability and managerial issues, equipping readers with the tools to navigate the complexities of AI-infused KM practices.

Providing a valuable resource for business leaders, academics, and students, these volumes support those looking to integrate AI into KM to drive strategic decision-making and operational efficiency. Merging traditional knowledge management practices with the latest AI advancements, they prepare readers to harness technology for innovative solutions, positioning their organizations for success in the modern business landscape.



About the Author



Meir Russ is a Professor Emeritus in Management at the Austin E. Cofrin School of Business at the University of Wisconsin-Green Bay, USA, a Research Fellow at the Stellenbosch University in South Africa and a Visiting Professor at the University of Lódź, Poland. He is presently the Editor-in-Chief of The Online Journal of Applied Knowledge Management (OJAKM).

Miltiadis Lytras is a Professor (Full) at The American College of Greece and a Visiting Research Professor at Effat University in Saudi Arabia. Dr. Lytras is a world-class expert in the fields of digital transformation and technology-enabled learning. He is an expert in advanced computer science and management, editor, lecturer, and research consultant, with extensive experience in academia and the business sector in Europe, the Middle East, and Asia.

Dimensions (Overall): 9.02 Inches (H) x 5.98 Inches (W)
Suggested Age: 22 Years and Up
Number of Pages: 400
Genre: Business + Money Management
Sub-Genre: Knowledge Capital
Publisher: Emerald Publishing Limited
Format: Hardcover
Author: Meir Russ & Miltiadis Lytras
Language: English
Street Date: March 16, 2026
TCIN: 1006415406
UPC: 9781805923923
Item Number (DPCI): 247-34-2649
Origin: Made in the USA or Imported

Shipping details

Estimated ship dimensions: 1 inches length x 5.98 inches width x 9.02 inches height
Estimated ship weight: 1 pounds
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