AI-Driven Circular Digital Supply Chains: An Integrated Framework for Sustainable Value Creation in Emerging Markets

Digital transformation has improved visibility and efficiency in supply chains, yet it has delivered limited progress toward circular economy objectives, particularly in emerging markets. Existing research has largely examined digital technologies in isolation or treated artificial intelligence (AI) as a secondary analytical tool, leaving unclear whether circular performance improvements stem from technology adoption itself or from changes in supply chain decision-making. This study addresses this gap by proposing the AI-Driven Circular Digital Supply Chain (AICD-SC) framework, which conceptualizes AI as a central decision orchestrator integrating predictive, prescriptive, and simulation-based capabilities to coordinate closed-loop supply chain processes. The study employs a sequential explanatory mixed-methods design, combining 17 semi-structured interviews with a quasi-experimental Difference-in-Differences analysis of eight manufacturing firms in Mexico and Colombia during 2023–2024. The results show that firms adopting AI-centric decision architectures achieved waste reductions of 18–26% and improvements in material reuse and recovery of 14–17%, while firms relying on digitally enabled but non–AI-centric configurations exhibited no statistically significant circular performance gains. These findings indicate that circular outcomes do not emerge from digitalization alone, but from how supply chain decisions are architected and orchestrated through AI. The study concludes by offering a phased adoption roadmap aligned with Sustainable Development Goal 12, providing actionable implications for managers and policymakers in emerging markets.