Abstract

Artificial intelligence, using deep learning, natural language processing, and image analysis technologies, has become a driving force in e-commerce. It improves transaction efficiency, reduces business costs, and enhances user experience. This paper collects application data from the AI e-commerce industry and, using the LDA topic model, summarizes the sample data into 12 topics. It then analyses AI e-commerce applications from the perspectives of information decision-making, operational applications, marketing promotion, and business analysis. Using K-means clustering, the paper integrates topic features with clustering results to identify 6 clusters. By combining the features of each cluster, it analyzes the development trends of AI e-commerce from perspectives including industry competition, ecological synergy, capital markets, smart grids, cross-border e-commerce, and industrial applications. Considering the industry’s risks and challenges, the paper proposes development strategies for AI e-commerce.

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