Human–AI symbiosis for resilient supply chains: a Delphi-fuzzy cognitive mapping analysis of an Indian textile sector

Abstract

Purpose The purpose of this study is to explore how artificial intelligence (AI) can augment rather than replace human decision-making in human-centric supply chains, and how this synergy enhances supply chain flexibility (SCF) and supply chain resilience (SCR), using a textile sector in North India as the real-world context. Design/methodology/approach The study is conducted in two phases. The first phase focuses on identifying and prioritizing the relevant AI-related and human-centric factors for the study, which is addressed through an exhaustive literature review for identification and then the Delphi method to prioritize them. The second phase focuses on modeling the relationship between these factors using fuzzy cognitive mapping (FCM) approach. Expert inputs are used to construct the causal structure and analyze the strength of interconnections. By modeling bidirectional and nonlinear relationships rather than assuming static, unidirectional causality, this method captures feedback dynamics, which conventional linear techniques cannot represent. Findings The results show that human-centric factors particularly human–AI augmentation, human–machine collaboration and workforce preparedness play a central role in translating AI capabilities into SCF and SCR. AI-related factors primarily act as drivers, while supply chain outcomes materialize through these human-centric mechanisms. Originality/value This study offers a mechanism-based explanation of AI-enabled supply chain performance and employs FCM to capture complex interrelationships within a sociotechnical system.