Artificial Intelligence Adoption in the Apparel Supply Chain in Sri Lanka: Strategies for Small and Medium-sized Enterprises

Abstract

Artificial Intelligence (AI) is rapidly transforming supply chain operations across industries, driving efficiency, cost reduction, and sustainability improvements. In Sri Lanka, large-scale apparel companies have successfully integrated AI into their supply chain processes, but small and medium-sized enterprises (SMEs) face significant challenges in adopting AI. This study focused on identifying these challenges in SMEs, particularly key financial, technological, and organizational barriers, by referencing AI practices in large-scale apparel companies. Data were collected through surveys, receiving responses from 156 participants representing 50 SMEs and 280 participants from 12 large-scale apparel companies. Analytical techniques, including descriptive statistics, qualitative analysis, cross-analysis, and graphical representation, were employed to analyze the data. The findings showed that AI adoption increases operational efficiency and competitiveness in the apparel sector, with technologies such as Machine Learning, Predictive Analytics, Robotic Process Automation (RPA), Internet of Things (IoT), and Computer Vision while revealing the barriers for SMEs, such as high initial investment costs, ongoing maintenance costs, limited technical expertise, and resistance to change. Based on these results, a strategic framework with actionable strategies was proposed to guide SMEs in overcoming these barriers and integrating AI technologies effectively into their supply chain operations. This research contributes to the broader AI integration in apparel supply chains, specifically in SMEs in developing economies like Sri Lanka.