Abstract: Artificial intelligence (AI) has demonstrated significant potential in transforming supply chain management (SCM) across industries, contributing to the economic, social, and environmental dimensions of sustainability. Despite this potential, research examining AI applications in sustainable SCM within small and medium enterprises (SMEs) remains scarce. In this light, this study conducts an exploratory literature review of 362 research publications between 2020 and 2025 using natural language processing (NLP) and data visualization techniques. Corpus distribution and frequency analyses indicate a rapidly growing research interest in the application of AI for sustainable supply chains for SMEs. Furthermore, Latent Dirichlet Allocation (LDA) topic modeling reveals a clear shift in the literature from general AI adoption toward specific applications and sustainability use cases, such as green energy transition, production waste reduction, green logistics, and circular economy. Notably, the findings position AI not merely as a tool, but as a key enabler of sustainability in SME supply chains. At the same time, the findings highlight persistent challenges faced by SMEs, especially in terms of organizational readiness, workforce capability, and technological uncertainty. Finally, the study offers implications at the theoretical, practical, and policy levels to support the integration of AI in sustainable SCM among SMEs.