Integrating GenAI into Corporate Knowledge Management: A Socio-Technical Approach to Overcoming Knowledge Management Challenges

Abstract

The growing importance of Artificial Intelligence (AI), especially Generative AI (GenAI), is revolutionising the way knowledge is handled and opening up enormous potential for corporate knowledge management (KM). The rapid development of Large Language Models (LLM) and complementary technologies such as Retrieval Augmented Generation (RAG) or knowledge graphs opens up new opportunities for corporate KM, but also presents companies with complex challenges and barriers. This study examines the integration of genAI into corporate KM, taking into account a holistic socio-technical approach. A AI4KM survey was designed to capture the current state of AI use by asking companies about their use of AI technologies. The survey aims to gain insights into the practical implementation of AI solutions, particularly in relation to KM challenges. Based on the results of the AI4KM survey, a socio-technical TOP approach (Technology - Organisation - People) for the introduction of AI-based KM will be developed, which takes into account not only technical, but also organisational and people-related aspects. By addressing these three factors, the study aims to provide a comprehensive framework that ensures the successful adoption of AI technologies in diverse business environments. Specific recommendations for the development of an effective, holistic AI strategy in KM are developed for the various barriers. Among other things, the importance of human-machine interaction will be emphasised in order to create a seamless link between human expertise and machine intelligence. The results of these studies should help companies, especially small and medium-sized enterprises (SME), to effectively use genAI technologies for their KM, to counteract the loss of knowledge due to demographic change and to increase their competitiveness. The combination of theoretical findings and practical recommendations will build a bridge between research and business practice, contributing to the successful integration of AI into corporate KM and equipping companies for the challenges of the future.