The Future of Knowledge Management in Family firms: Factors and Barriers for AI Adoption

Abstract

Family businesses represent the most widespread entrepreneurial form. Within knowledge management studies, a large amount of research has focused on family businesses, highlighting the particular needs they require. At the same time, several studies have highlighted the existence of barriers and enabling factors in the adoption of new technologies within family businesses. Currently, we are seeing the spread of artificial intelligence (AI) within business organizations. On these premises, this study has a dual objective. The first objective, from a theoretical point of view, wants to trace the link between AI and knowledge management. The second objective of this study aims to identify the main barriers to the application of AI in family businesses. This study is based on a systematic literature review using the phases of data collection, bibliometric analysis and content analysis. Two international scientific databases were used: Scopus and Web of Science (Clarivate). A search string was created by identifying keywords. Subsequently, only scientific documents published in double blind review journals, in English, were selected. The sample used in this study contained about 40 scientific documents. The results of this study offer initial reflections on the adoption of artificial intelligence in family businesses. Artificial intelligence represents a new way of managing knowledge within organizations. The peculiar characteristics of family businesses impose reflections on the methods of adoption and barriers that may emerge. This study contributes to the understanding of family businesses, under the theoretical perspective of knowledge management. Family businesses represent complex but widespread organizations. For this reason, academics, entrepreneurs and practitioners must understand the obstacles that could make the adoption of AI difficult.