Artificial Intelligence as a Catalyst for Environmental and Social Sustainability Practices in SMEs: The Moderating Role of Sustainability, Digitalization, and Innovation Barriers

Abstract

This study examines the relationship between artificial intelligence and both environmental and social sustainability practices in small and medium-sized enterprises, with a specific focus on the moderating effects of implementation barriers relating to sustainability, digitalization, and innovation. Drawing on resource-based view and contingency theory, the relationship and moderating effects are analyzed empirically utilizing data from the Flash Eurobarometer 486 survey, covering 12,632 small and medium-sized enterprises across 39 countries. Employing ordinary least squares regression with interaction terms, the findings reveal a significant positive relationship between artificial intelligence adoption and both environmental and social sustainability practices in small and medium-sized enterprises. However, this relationship is moderated by the implementation barriers, with higher barriers weakening the positive relationship between artificial intelligence and both environmental and social sustainability practices. This study contributes to the growing body of literature on artificial intelligence and sustainability in small and medium-sized enterprises by providing novel empirical evidence on their relationship and, uniquely, on the moderating role of implementation barriers related to sustainability, digitalization, and innovation, an aspect previously unexplored. The results offer important implications for small and medium-sized enterprise managers, policymakers, and researchers, highlighting the need for tailored strategies to overcome barriers and effectively implement artificial intelligence for enhanced environmental and social sustainability practices.