AI adoption in small and medium-sized e-commerce enterprise: current state and future research agenda

Abstract

Artificial intelligence (AI) is being increasingly used in digital commerce. It helps small and medium-sized enterprises (SMEs) improve efficiency, enhance customer engagement, and support data-based decisions. However, research on AI adoption in SME e-commerce is still in emerging stage. This study aims to synthesize existing work and identify key applications, drivers, and constraints. The study uses a systematic literature review (SLR) based on the PRISMA framework. Relevant studies were identified, screened, verified, and included from major databases using PRISMA. A total of 92 peer-reviewed articles were selected and analysed using thematic analysis. The findings show that SMEs have yet leveraged very limited capabilities of AI for business operations. Common applications include chatbots, recommendation systems, predictive analytics, and AI-enabled CRM tools. Key contributor to adoption is technological, organizational, and environmental factors. While AI offers benefits such as cost efficiency and improved decision-making, challenges such as limited infrastructure, skill gaps, and governance concerns persist. The study aims integrating diverse literature and presents in unified format in context of AI adoption in case of SMEs in e-Commerce. Key theories such as TOE, Dynamic Capabilities, Diffusion of Innovation, and Resource Dependency Theory and their interrelation is discussed. Finally, research gap and scope for Future research is presented.