The AI-Pivoting SME: How Small and Medium Enterprises Leverage Artificial Intelligence for Business Model Innovation and Competitive Advantage

Abstract

Small and Medium Enterprises (SMEs) are crucial to global economies, but their adoption of Artificial Intelligence (AI) lags behind larger firms. This study aims to address this gap by developing a comprehensive model for AI adoption in SMEs. The study seeks to integrate the Technology-Organization-Environment (TOE) model with the Diffusion of Innovations (DOI) model to understand AI adoption in SMEs. It also aims to test the causal relationships between AI adoption and Business Model Innovation (BMI) and Competitive Advantage (CA). The study uses survey data from 305 SMEs and applies Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse the relationships between AI adoption determinants and business outcomes. The findings show that market pressures and sustainable human capital are the strongest predictors of AI adoption. Financial limitations are less impactful due to the availability of low-cost AI solutions. AI adoption significantly enhances economic performance, with a strong correlation between AI and revenue growth. AI is a strategic enabler for SMEs to achieve BMI and CA. The study proposes a six-phase roadmap for AI implementation, emphasizing talent development and responsible AI governance. Future research should explore the long-term dynamics of AI adoption in SMEs.