Transforming Global Supply Chains through Artificial Intelligence, Automation, and Circular Economy Principles

Abstract

The transformation of global supply chains (GSCs) is accelerating due to the convergence of emerging digital technologies, sustainability imperatives, and innovative business models. Artificial intelligence (AI), automation, and circular economy (CE) principles are increasingly being integrated to create supply networks that are not only intelligent and adaptive but also resilient and environmentally sustainable. This review synthesises the latest research on the application of AI and automation in facilitating circular and resilient supply chains, examining both theoretical and empirical studies. It explores technological innovations such as predictive analytics, robotics, digital twins, and smart logistics systems, and demonstrates how these tools can enhance operational efficiency, reduce waste, and extend asset lifecycles in line with CE principles. The paper also analyses operational implications, including improved decision- making, transparency, traceability, and multi-tier collaboration, while identifying the challenges and barriers firms face, such as high implementation costs, data quality issues, interoperability concerns, and regulatory constraints. Furthermore, the review highlights opportunities for integrating AI-driven automation with circular strategies to foster sustainable value creation and long-term competitiveness. Finally, it outlines future research directions, emphasising longitudinal studies, socio-technical impacts, cross-sectoral analyses, and the development of robust governance and measurement frameworks. By providing a comprehensive overview, this review offers actionable insights for academics, industry practitioners, and policymakers seeking to drive the adoption of technology-enabled, circular, and resilient supply chains in a rapidly evolving global economy.