Integrating AI in Sustainable Supply Chain Practices: Comparative Analysis between the USA and Europe

AI has slowly become relevant in SCM to improve the performance of corporations, for cost saving and customer satisfaction in the supply chain.Nevertheless, it is crucial to notice that the applicability and effectiveness of AI as a means to enhance supply chain performance can be highly contingent on multiple factors including technological environment, data quality and workforce competencies in different sectors and regions.This research seeks to address this issue by undertaking a comparative study of the effects of AI on supply chain performance of MNCs in two regions, namely the USA and Europe.The study adopts the Resource-Based View (RBV), Technology-Organization-Environment (TOE) framework, Diffusion of Innovations (DOI) theory, and Systems Theory to examine the impact of integrating AI on the supply chain performance indices such as order processing time, inventory, cost, customer satisfaction, and delivery accuracy.The study employs a quantitative method with secondary data collected through corporate reports.The research proves that the AI integration enhances the supply chain performance by reducing the order processing time, inventory, and supply chain costs and enhancing customer satisfaction and other aspects such as delivery accuracy.The use of AI, however, differs across industries and geographical locations, success factors that are crucial include the quality of data, technology, support from the top management, training of employees and an effective implementation plan.These insights may be useful for C-level managers in MNCs who are trying to determine how to harness AI technologies to generate value in a fast and volatile global environment.