Knowledge Management in the AI Era: Evolution, Challenges and Strategic Adaptation

Why Knowledge Management Matters in the Artificial Intelligence Era: In an age where Artificial Intelligence (AI) is revolutionising industries, knowledge is no longer static; it is dynamic, evolving, and increasingly intertwined with intelligent systems. Knowledge management (KM), once centred on human expertise and structured repositories, has reached a pivotal moment where AI is not just a tool for efficiency but a force reshaping how knowledge is created, shared, and applied. This book explores the transformative impact of AI on KM, uncovering both the opportunities and challenges that arise as organisations adapt to an era of intelligent knowledge ecosystems. For decades, KM relied on paper-based records, institutional memory, and traditional databases. With the rise of digital transformation (DT), information became more accessible, structured, and retrievable. However, the emergence of AI has fundamentally altered this landscape, shifting from static information management to dynamic, self-improving systems that can learn, predict, and generate insights autonomously. Machine learning (ML) algorithms now extract hidden patterns from vast datasets, while natural language processing (NLP) enables seamless human-machine interaction. AI-driven expert systems also contribute to decision-making processes. These advancements challenge conventional understandings of knowledge, raising critical questions: What constitutes knowledge in the era of AI? How does AI reshape the way knowledge is created and shared? What are the risks and ethical implications of relying on machine-generated knowledge? This book aims to provide a comprehensive exploration of KM in the AI era by addressing these critical questions. It examines how KM has evolved in response to AI and DT, redefines knowledge in the context of intelligent systems, and analyses how AI enhances or disrupts traditional knowledge-sharing practices. It also critically evaluates the risks, biases, and ethical concerns associated with AI-driven KM, while offering strategic insights on how organisations can adapt to this rapidly evolving landscape. By engaging with these themes, this book serves as a guide for scholars, business leaders, and knowledge professionals seeking to navigate and leverage AI in their KM strategies. Importantly, this book bridges theory and practice, offering empirical insights that matter deeply to real-world decision-makers. For small and medium-sized enterprises (SMEs), the findings reveal how AI can democratise access to strategic knowledge, helping them compete more effectively against larger firms by leveraging data-driven insights, automating knowledge workflows, and enhancing innovation capabilities. For managers and leaders, this work highlights the skills and cultural shifts necessary to successfully embed AI into KM practices, including fostering trust in AI-generated knowledge, mitigating biases, and ensuring ethical stewardship of knowledge assets. Moreover, for practitioners and consultants, it outlines actionable frameworks and decision-making tools to design adaptive knowledge ecosystems that are resilient, inclusive, and future-ready. Through real-world case examples, conceptual models, and strategic recommendations, the book offers a roadmap for organisations of all sizes to not merely survive but thrive in the AI-driven knowledge economy. AI is not merely a technological advancement; it is a paradigm shift that will define the future of knowledge work. Organisations that fail to integrate AI into their KM strategies risk inefficiency, knowledge fragmentation, and missed opportunities. Conversely, those that embrace AI-driven KM will unlock new capabilities, from predictive analytics to real-time knowledge generation, fostering enhanced collaboration, innovation, and decision-making. This book is not just about technology; it is about the very nature of knowledge in the AI age and its profound implications for organisations, researchers, and policymakers. As AI becomes an integral part of how knowledge is created, stored, and utilised, understanding its role in KM is no longer optional; it is essential. This book provides the insights and frameworks necessary to navigate this transformation, offering a forward-looking perspective on how AI is shaping the knowledge landscape and what it means for the future of KM.