The article was featured in ICSB’s Journal for Small Business Management (JSBM).
Authors: Anna Peters, Dominik K. Kanbach, Sascha Kraus and Paul Jones
The recent surge in adopting artificial intelligence (AI) by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, the existing literature reveals a fragmented landscape that hinders our understanding of how SMEs use AI. We address this through a systematic literature review wherein we analyze 106 peer-reviewed articles on AI adoption in SMEs and categorize states and trends into eight clusters: (1) compatibility, (2) infrastructure, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, and (8) ecosystem: according to the technology–organization–environment model. Our research provides valuable insights and identifies significant gaps in existing literature, notably overlooking trends identification as a pivotal driver and neglecting legal requirements. Our study clarifies AI implementation within SMEs, offering a holistic and theoretically grounded perspective to empower researchers and practitioners to facilitate more effective adoption and application of AI within the SME sector.
Within the dynamic landscape of science and technology, artificial intelligence (AI) has emerged as a catalyst reshaping our interactions with technology, our problem-solving methods, and even our comprehension of intelligence itself (Giuggioli & Pellegrini, Citation2023). Despite the vast potential of AI, its integration within small and medium-sized enterprises (SMEs) faces considerable hurdles, notably the challenges of change management (Nagy et al., Citation2023). Overcoming these challenges and fostering AI adoption is imperative for SMEs to thrive (Lemos et al., Citation2022).
Critically, boosting AI use within SMEs requires navigating the complexities inherent in identifying suitable AI technologies and applying them across an array of organizational functions and deployment scenarios (Hansen & Bøgh, Citation2021). The literature on applying AI in SMEs, while abundant, often lacks coherence and comprehensiveness (bin Ahmad et al., Citation2019; Giuggioli & Pellegrini, Citation2023; Treiblmaier, Citation2018). This is unfortunate, as AI adoption by SMEs has substantial potential benefits ranging from productivity enhancements to cost reductions to improved employee experiences (Chaudhuri et al., Citation2022).
Failure to embrace AI could have dire consequences for SMEs, including lost competitiveness and market share, diminished economic influence, and reduced employment opportunities (Baabdullah et al., Citation2021). While AI adoption strategies vary, they typically involve increasing investments, automating processes, and upgrading systems and technologies to remain competitive (Hansen & Bøgh, Citation2021). It is essential to note, however, that overly complex AI applications may not be feasible for SMEs because of their cost and complexity (Moeuf et al., Citation2020).
Read More (click here).
