Integrating Artificial Intelligence and Circular Economy Principles for Resilient and Regenerative Supply Chains: A Comprehensive Framework and Empirical Analysis

The convergence of artificial intelligence (AI) and circular economy principles presents unprecedented opportunities for transforming supply chain management from linear, resource-depleting models to regenerative, resilient systems. This study develops and validates a comprehensive framework integrating AI-driven technologies with circular economy principles to enhance supply chain resilience and environmental regeneration. Through systematic analysis of 245 manufacturing organizations across electronics, automotive, and fashion industries from 2020-2024, we examine how AI enables product lifecycle tracking, reverse logistics optimization, and predictive waste minimization. The research employs mixed-methods approach combining structural equation modeling, machine learning algorithms, and case study analysis. Results demonstrate that AI-circular integration significantly improves supply chain resilience (β = 0.742, p < 0.001), reduces environmental impact by 34.6%, and enhances regenerative capacity by 28.3%. The study contributes a novel AI-Circular Resilience Framework (ACRF) with validated metrics for measuring regenerative performance and provides actionable roadmaps for industry implementation.