Title: Generative artificial intelligence for adopting circular economy in supply chains: opportunities, challenges, and future pathways

Authors: Salim Eray Celik; Zhuowen Chen; Abdullah Yildizbasi; Joseph Sarkis

Addresses: School of Business, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA ' School of Business, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA ' University of Alabama-Huntsville, Huntsville, Alabama, USA ' School of Business, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA; LAMIH Laboratory, Université Polytechnique Hauts-de-France, Campus Mont Houy, Valenciennes, 59313, France

Abstract: The circular economy (CE) and generative artificial intelligence (GenAI) can work together to address supply chain sustainability and sustainability issues generally. We provide a perspective on how GenAIs core capabilities - technical intelligence, creative and cognitive augmentation, decision intelligence, and interaction - may enable CE implementation using the ReSOLVE CE framework. Regenerative agriculture, corporate logistics, product design, and waste valorisation are some practice areas that will be used to illustrate how GenAI can support narrowing, slowing, and closing resource loops - central principles of CE. Critical challenges - such as limited GenAI circular awareness, social and environmental concerns, and validation - may also constrain GenAI in CE and by extension to sustainable supply chains. Within this context, a forward-looking research agenda is proposed using various theoretical perspectives. This perspective aims to guide scholars, practitioners, and policymakers in leveraging GenAI as a catalyst for regenerative, inclusive, and scalable circular supply chains and a sustainable CE.

Keywords: generative artificial intelligence; GenAI; circular economy; supply chain management; ReSOLVE; sustainability.

DOI: 10.1504/IJGAIB.2026.151818

International Journal of Generative Artificial Intelligence in Business, 2026 Vol.1 No.1/2, pp.8 - 35

Received: 31 Jul 2025
Accepted: 06 Aug 2025
Published online: 20 Feb 2026 *