With the growth of globalization and digitalization, cross-border e-commerce(CBEC) has become an important part of international trade. Traditional data analysis methods have problems such as low efficiency and lack of accuracy when processing CBEC big data, which makes it difficult to meet the actual needs of enterprises. Therefore, this paper proposes to use artificial intelligence technology to build a CBEC big data analysis model. First, the background of CBEC big data is introduced, and then the research content of relevant scholars is reviewed, and the shortcomings of current research are pointed out. Next, this paper elaborates on the construction method of CBEC big data analysis model based on artificial intelligence, preprocesses e-commerce data, selects features, and trains the model. Through experimental investigation, this paper verifies the data coverage and analysis accuracy of the proposed model. Experimental results show that the CBEC big data analysis model based on artificial intelligence can significantly improve the efficiency and accuracy of data analysis. The data are all between 80% and 100%, showing an upward trend. The model demonstrates powerful data analysis capabilities and can provide strong decision-making support for enterprises. At the same time, the model can also discover potential market trends and consumer behavior patterns, providing a strong basis for the optimization of corporate market strategies.