AI-Driven Supply Chain Adaptation: A Cross-Cultural Analysis of COVID-19 Impacts on Online Supermarkets in China and the UK

The new Corona epidemic had a huge impact on the global retail industry, leading to a significant acceleration in the rate of transformation of the artificial intelligence-driven supply chain. This study combines a hybrid method with a large scale cross-cultural context research (sample size N=100) to try to analyze the changing structure of online supermarkets in response to external disturbances. Chinese data shows that Jingdong achieved a 215% increase in order volume (significance level p<0.01) during the period of the strictest quarantine measures, while Tesco in the UK applied a route planning function using artificial intelligence, which significantly reduced delivery time by 40% (significance level p=0.03).There are obvious differences in consumer relationship rates across cultures: British consumers prefer to monitor supply chain management using blockchain (or a value of 2.1), while Chinese feedback suggests that they favor solutions with dynamic prices (the coefficient β is 0.48).Face the challenges they face during this change, the level of network security risk has risen to 30% (significance level p=0.03), and hidden ethical hazards caused by unscrupulous use of algorithms have also become a major problem in this area (Wang, Zhang, 2024).This study uses the Toe concept to present a revised version that adapts to current variables that take cultural adaptation into account and proposes a new and effective integrated federal training model that can provide technical support to reduce e-commerce emissions by less than 22% (Gupta et al.2007)., 2024). to achieve successful research of a model that meets the requirements of AI in the digital age in accordance with Sustainable Development Goal 9 and creates a flexible environment in accordance with the requirements of AI.