Adopting artificial intelligence in small and medium businesses: the knowledge-based perspective

Abstract Artificial Intelligence (AI) has emerged as a key technology that small and medium businesses (SMBs) utilize to process big data, use robots for industrial and service objectives and be able to grow, innovate and collaborate given the paucity of resources. This study examines how investments in organizational, technological and external (environmental) knowledge shape AI adoption following the Technology – Organizational – Environment (TOE) theoretical framework for technology adoption. We investigate the effect of adoption of two types of AI: application-oriented AI (robotics) and learning- and invention-oriented AI (machine learning and big data analysis). We evaluate the interplay between an SMB’s investment in internal R&D, digital technologies and external knowledge in the form of R&D purchase, knowledge spillovers and collaboration with external partners altogether explaining propensity to adopt AI. We use micro-level data from three combined surveys from the SMBs in the UK during 2010–2020 using regression analysis and selected qualitative data. Our findings demonstrate that investment in internal and external knowledge including spillovers and knowledge collaboration directly affects the propensity of SMBs’ to adopt AI for both robotics and big data analysis. We also find that recombination of internal and external knowledge reduces AI adoption propensity and discuss why.