Transforming Knowledge Management through Synergistic AI-Human Collaboration

Authors: Viraj Dawarka, Geshwaree Huzooree
Cited by: 0

Abstract

As organisations increasingly navigate the complexities of the digital age, the incorporation of Artificial Intelligence (AI) into knowledge management (KM) frameworks is becoming indispensable for the attainment of sustained competitive advantage. This chapter explores the transformative capabilities of AI within KM, underscoring the pivotal significance of human-AI collaboration. We will investigate how emerging technologies, including AI, machine learning (ML) and natural language processing (NLP), can enhance key KM dimensions: the creation, storage, retrieval, sharing, and application of knowledge. Furthermore, the chapter considers the essential contributions of human expertise, contextual understanding, and decision-making in KM practices. By elucidating the synergy between the advantages of AI, like scalability, data analysis, human competencies, creativity and empathy, the chapter further explores specific implementations of AI-human collaboration, encompassing automated knowledge repositories for knowledge generation, NLP for knowledge retrieval, and tailored recommendations for knowledge application. We will also address the ethical challenges and implications that accompany AI integration, focusing on issues such as bias, the need for transparency, trust in AI systems, data privacy, and the balance between human oversight and AI control. Finally, we outline practical implications for organizations aiming to empower talent, create AI-friendly infrastructures, and streamline knowledge processes to foster successful human-AI partnerships. We conclude by discussing the future of AI-human collaboration in KM, identifying emerging trends and the long-term benefits of integrating AI into organisational learning and innovation.

Fields of Study & Subjects

Knowledge Management and Technology Artificial Intelligence Applications AI and HR Technologies

Publication details

Journal / source
Staffordshire Online Repository (Staffordshire University)
Publication date
16 March 2026