Abstract: With the rise of the digital economy and artificial intelligence (AI), data analysis has become a core driver of transformation and development in the field of economics. This paper focuses on the field of international trade, summarizing and analyzing the content and requirements of trade data analysis to provide a solid foundation for academic research, policy evaluation, corporate decision-making, and media interpretation. Research in international trade relies on both rigorous theoretical frameworks and abundant practical data. Against this backdrop, cultivating interdisciplinary professionals who master new ways of thinking, new theories, and new tools is particularly important. While AI technology has significantly enhanced analytical efficiency in areas such as data retrieval and chart generation, core insights and innovative frameworks still require the guidance of researchers' critical thinking and industry experience. Therefore, it is necessary to develop targeted disciplinary teaching plans that incorporate the characteristics of AI, thereby promoting the high-quality development of the international trade discipline toward digitalization and intelligence, and cultivating multidisciplinary talents with an international perspective, practical skills, and an innovative spirit.
