...The rapid evolution of artificial intelligence (AI) has transformed how organisations define, structure, and apply knowledge, challenging traditional frameworks in knowledge management (KM). Classical distinctions such as tacit and explicit knowledge, along with established models like the SECI...

...The convergence of artificial intelligence (AI) and knowledge management (KM) marks a paradigm shift in how organisations capture, distribute, and apply knowledge to drive innovation and competitiveness. Traditional KM systems, while effective in codifying and disseminating explicit knowledge...

...This chapter explores how organisations can strategically adapt to the integration of artificial intelligence (AI) in knowledge management (KM). It argues that successful adoption requires more than technological deployment; it demands alignment of strategy, structure, and culture to create...

...The evolution of knowledge management (KM) reflects humanity's continuous effort to collect, preserve, and apply knowledge to drive innovation and competitiveness. From ancient oral traditions and apprenticeship models to structured repositories and digital platforms, KM has undergone significant...

...While artificial intelligence (AI) has introduced unprecedented opportunities in knowledge management (KM), its integration into organisational knowledge ecosystems presents significant challenges. Chief among these are issues of data quality, algorithmic bias, privacy, and security. AI-driven KM...

...The future of artificial intelligence (AI) in knowledge management (KM) is expected to redefine how organisations create, share, and apply knowledge. This chapter examines key directions for AI-enabled KM, including hyper-personalisation of knowledge delivery, predictive analytics for decision...

... significant organizational transformation. These changes center on three main components: people, infrastructure, and processes. Knowledge management (KM) involves several key processes, including knowledge creation, storage and retrieval, sharing, and application. AI capabilities can support each...

...Abstract This chapter explores the implementation of artificial intelligence (AI) for knowledge management (KM) in small and medium enterprises (SMEs). Compared with larger corporations, SMEs frequently encounter limits to their capacity to adopt comprehensive KM strategies due to limited access...

...Abstract In today’s competitive and complex business landscape, the integration of artificial intelligence (AI) into knowledge management (KM) systems presents transformative opportunities for enhancing talent management (TM) strategies. This chapter explores the pivotal role of AI-driven KM...

... to encounter inadequate datasets, data separation and the lack of variety in information provided by organisations. This limits AI opportunities and may lead to biases or other errors in KM systems ( Davenport & Prusak, 2000 ). Data Quality and Accessibility AI Integration Issues in Knowledge Management...

...Abstract While the integration of artificial intelligence into knowledge management holds transformative potential for businesses, it also introduces a range of ethical risks, security vulnerabilities, and opportunities for misuse. As AI-generated knowledge becomes an asset, it also...

...Abstract The rapid evolution of Artificial Intelligence (AI) is reshaping the landscape of Knowledge Management (KM) in modern businesses. As AI technologies mature and permeate operational and strategic layers of organizations, they enable dynamic knowledge processes that are more adaptive...

...Abstract Knowledge management (KM) as a multidisciplinary approach enables the realization of organizational objectives by unleashing the full potential of knowledge and providing the correct information to the right audiences at the right time. The world has seen the emergence of Artificial...

...Abstract The chapter considers the ethical and managerial implications of integrating generative artificial intelligence (Gen AI) into the Knowledge Management (KM) processes. The introduction of various Gen AIs, such as ChatGPT, GPT-3, GPT-4, DALL-E2 and others, in recent years...

...Abstract This chapter describes professional experiences gleaned from about 50 business-related knowledge management projects, where artificial intelligence (AI)-based processes were successfully used to complement and augment human intelligence (HI). These projects covered a broad swathe...

... culture. Specifically, it highlights the strategic role of L&D units as facilitators in GenAI adoption processes, thereby contributing to a broader understanding of GenAI-enabled knowledge management strategies. Generative AI organizational culture learning and development units organizational...

...Abstract Integrating Artificial Intelligence (AI) in Knowledge Management (KM) represents a transformative approach to how firms acquire, retain, and utilize knowledge to sustain competitive advantages. This chapter examines the key role of AI in enhancing six KM capacities—inventive, absorptive...

...Abstract Artificial Intelligence (AI) systems have become an integrated part of almost every aspect of contemporary organizations’ work environments. At a time when AI changes the way organizations acquire, create, and share knowledge, AI-driven Knowledge Management (KM) requires the re-evaluation...

...Abstract As artificial intelligence (AI) becomes an integral component of knowledge management systems (KMS), organizations face a new spectrum of vulnerabilities, including fraud, misuse, and ethical threats. This chapter explores these challenges within the evolving landscape of AI-driven KMS...

... impact. The main theoretical and management implications are discussed. Servicescape accommodationscape knowledge management hospitality eWOM Introduction The hotel under review is part of an international group of hotels and is a leading name in luxury hospitality and contemporary lifestyle...