Artificial Intelligence for Sustainable and Climate-Resilient Apparel Supply Chains: A Narrative Review and Integrative Framework

Abstract

This study examines the role of artificial intelligence (AI) in enhancing environmental sustainability and climate resilience in apparel supply chains. Although prior research has extensively explored sustainable supply chain management, circular economy practices, and AI-driven supply chain resilience, these streams remain largely fragmented. To address this gap, this paper adopts a narrative review approach, analyzing 25 peer-reviewed studies published between 2015 and 2021 across databases including Scopus, Web of Science, and Google Scholar. The findings reveal that apparel-specific research is strong in identifying sustainability challenges, such as environmental degradation, labor issues, and governance complexity, while AI and resilience studies provide advanced insights into predictive analytics, optimization, and risk management but are predominantly situated in general supply chain contexts. There is a clear lack of integration among AI capabilities, environmental sustainability, and climate resilience within apparel supply chains. This paper contributes by synthesizing these disconnected streams and proposing an integrated perspective that links AI technologies to supply chain functions, sustainability outcomes, and resilience capabilities. The study highlights that AI can serve as a bridging mechanism by improving forecasting, resource efficiency, and proactive risk management, while also identifying key barriers such as data limitations, lack of transparency, and organizational readiness. The findings have important implications for researchers, managers, and policymakers seeking to develop greener, more resilient apparel supply chains.