Adopting Artificial Intelligence in Apparel Supply Chains: Opportunities and Barriers in a Developing Economy

As Artificial Intelligence (AI) increasingly transforms global supply chain management (SCM), the Sri Lankan apparel industry—one of the nation’s key economic pillars—faces growing pressure to sustain its global competitiveness. However, the heavy concentration of AI resources and investments in advanced economies has widened the technological divide, leaving developing nations like Sri Lanka at an early stage of AI adoption. This study explores the potential applications and hidden challenges of adopting AI within Sri Lanka’s apparel supply chains (SLASC). Guided by a qualitative and exploratory research design, a preliminary assessment confirmed the nascent stage of AI implementation in the sector. Accordingly, a purposive sampling method was employed to select eight industry experts from the Board of Investment (BOI)-registered apparel manufacturers that had initiated Industry 4.0–related efforts and ranked among the country’s  top  twenty  apparel  exporters. These  experts, all  holding managerial positions in  digitalization functions, participated in semi-structured virtual interviews. Data saturation was achieved after eight interviews, and the data were thematically analyzed using NVivo 12 Pro. The findings reveal several emerging applications of AI in SCM—such as demand forecasting, predictive maintenance, and quality control—alongside key barriers including skill shortages, infrastructural gaps, high implementation costs, and data governance concerns. The study provides strategic insights for managers to align AI initiatives with organizational readiness and policy recommendations to bridge infrastructural and capability divides. Ultimately, the research emphasizes the urgent need for a structured strategic roadmap to facilitate AI-driven transformation across Sri Lanka’s apparel supply chains.