With the growing complexity of global supply chains, geopolitical events, pandemics, and just-in-time processes, organizations can benefit immensely in managing supply chain risks by adopting artificial intelligence (AI). Building upon past research in technology adoption, we study factors influencing the adoption intention of AI in SCRM across organizations in India. Based on a qualitative study, we discuss the applications and uniqueness of AI adoption in the field of supply chain risk management (SCRM) and propose a research model on the adoption, implementation, and routinization intention of AI in SCRM at an organizational level. Secondly, we discuss the implications of the study and the benefits to decision-makers and supply chain planners in devising effective strategies when adopting AI in SCRM.

The study aims to examine factors that influence the adoption-diffusion process of Artificial Intelligence (AI) in Supply Chain Risk Management (SCRM) across manufacturing, wholesale trade, retail trade, and transportation industries in India. As part of this study, eleven constructs that influence the adoption-diffusion stages of AI in SCRM were identified and examined. A survey was conducted to collect data from supply chain executives, risk professionals, and AI consultants across the manufacturing, wholesale trade, retail trade, and transportation industries in India. Partial least squares structural equation modeling (PLS-SEM) was used to study the data. Results show that these factors have varying degrees of influence and direction on the three stages of adoption of AI in SCRM. The study will enable the leadership team in the organizations to build a roadmap for the adoption, implementation, and routinization of AI in SCRM.

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