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.
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.
Part
1. Introduction
Chapter
1. The New Era of Artificial Intelligence in Knowledge Management:
Framing the Foundations of Intelligent Processes; Meir Russ and Miltiadis D.
Lytras
Part
2. The Role of AI in Enhancing Knowledge Management Processes
Chapter
2. The Role of AI in Enhancing Knowledge Management Processes; Tamer
Fahmy, Richa Minda, and Stephen Pak
Chapter
3. The Ethical and Managerial Implications of Integrating Generative
Artificial Intelligence into Knowledge Management Processes; James Osabuohien
Odia
Chapter
4. Artificial Intelligence-Based Risk Identification in Supervision
Reports of the Ministry of Health; Avital Zadok and Daphne Ruth Raban
Part
3. AI and Knowledge Discovery: Techniques and Applications
Chapter
5. Effectively Informing Policies with Digital Twins, AI and Digital
Technologies; Giovanna Di Marzo Serugendo
Chapter
6. The Complementary Roles of AI and Human Intelligence (HI) in
Business Knowledge Management; Khoon Chin
Chapter
7. AI and Knowledge Management: Navigating the Misinformation Maze;
Liz Kheng and Mark D. Schriml
Chapter
8. Transforming Knowledge Management with AI: Leveraging
Retrieval-Augmented Generation (RAG) in Business Strategy; Yiyuan Ava Liu and
Wanxi Li
Part
4. Machine Learning for Organizational Learning and Knowledge Sharing
Chapter
9. Learning and Development (L&D) Units and Organizational Culture:
Impacts on GenAI Adoption in Israeli Organizations; Gila Kurtz, Eran Gal,
Einav Yehilaviz, and Shachar Mahalal
Chapter
10. Enhancing Business Education with the Knowledge Management
Mesosystem Model: A Framework for Active Learning, AI Integration, and
Knowledge Sharing; Shanzhen Gao and Weizheng Gao
Part
5. Ethical Considerations in AI-Driven Knowledge Management
Chapter
11. Ethical Considerations in AI-Driven Knowledge Management:
Navigating Challenges in the Modern Business Landscape; Theophilus Kofi
Anyanful
Chapter
12. Who Can? AI Can! Enhancing Firms Knowledge Management
Capabilities Through an Ethical Implementation of Artificial Intelligence;
Soode Vaezinejad, Christopher Michael Starkey, and Dara Schniederjans
Chapter
13. Biases and Ethical Considerations in AI-Driven Knowledge
Management; Ruti Gafni, Boris Kantsepolsky, and Sofia Sherman
Part
6. Conclusions
Chapter
14. The Way Forward: A Roadmap for the Effective Adoption of
AI-Driven Knowledge Management Strategies in Business; Miltiadis D. Lytras
and Meir Russ
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 ód, Poland. He is presently the Editorin-Chief of The Online Journal of Applied Knowledge Management (OJAKM).
Miltiadis D. 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.
