Reconceptualizing Tacit Knowledge Transferring in the Age of AI and Human Collaboration
Artificial intelligence (AI) is transforming how organizations manage and distribute knowledge. AI-powered systems can efficiently store, retrieve, summarize, and recommend information across organizations. While AI performs well in handling explicit knowledge, such as documents, reports, and databases, it remains limited in capturing and transferring tacit knowledge. This study focuses on the continuing importance of human interaction in supporting tacit knowledge sharing and experiential learning within AI-enabled workplaces. As organizations increasingly rely on AI and digital workflows, opportunities for interpersonal knowledge exchange may decline, creating risks of knowledge loss and reduced experiential learning. Therefore, this study will investigate how human interaction remains essential in transferring tacit knowledge despite advances in AI technologies. Specifically, it aims to answer the following research questions: 1) What organizational practices best enable tacit knowledge transfer in AI-enabled workplaces? 2) How can organizations combine AI technologies with human-centered practices to support tacit knowledge transfer? This study is expected to contribute to the growing discourse on AI and knowledge management by highlighting the critical role of human intervention in AI-enabled workplaces and examining how the transfer of different forms of tacit knowledge can be effectively facilitated. The findings are anticipated to inform organizational strategies that integrate AI capabilities with interpersonal learning processes. In addition, the study may offer practical guidance for organizations seeking to preserve institutional knowledge and sustain innovation in increasingly automated work environments.