Toward Circular Economy and Intelligent FSCs: A Critical Review of AI-Driven Sustainability Transformation

Abstract

The global fashion industry is at a critical juncture, where increasing environmental challenges and rapid digital innovation are reshaping supply chain systems. This study provides a comprehensive review of the evolution of circular and intelligent FSCs by integrating artificial intelligence (AI) with circular economy (CE) principles. Using a narrative synthesis approach, the research analyzes 58 peer-reviewed studies published between 2020 and 2026, focusing on sustainability, supply chain management, and emerging digital technologies. The findings reveal a significant transition from traditional sustainability discourse toward AI-driven, system-level transformation. Technologies such as machine learning (ML), big data analytics, and the Internet of Things (IoT) enhance predictive capabilities, operational efficiency, and resource optimization. However, the analysis also identifies critical limitations, including a persistent gap between the theoretical potential of AI-enabled sustainability and its empirical validation in real-world applications. Furthermore, the literature demonstrates a strong emphasis on environmental sustainability, with comparatively limited attention to social dimensions such as labor conditions and ethical sourcing. To address these challenges, this study proposes the Technology–Sustainability Integration Model (TSIM), a socio-technical framework that conceptualizes sustainable transformation as the alignment and co-evolution of technological and sustainability maturity. The model highlights the importance of integrating digital capabilities with multidimensional sustainability practices to enable fully circular and intelligent supply chains. By synthesizing existing knowledge, identifying key research gaps, and offering a structured conceptual framework, this study contributes to advancing research and practice in sustainable fashion supply chain transformation.