With the rapid development of science and technology and the widespread application of the Internet, there is a wide range of online goods. At the same time, the continuous development of artificial intelligence (AI) has made online shopping more convenient, fast and cost‐effective and has become one of the popular shopping methods. Online shopping gives consumers more freedom of choice, and the homogenization of online products increases the cost of choice for consumers, while AI recommendation systems can also reduce costs. Based on this, the focus of this article is on the impact of AI recommendations for homogeneous online products on consumer demand. This article starts from the perspective of network homogenization products, and through relevant literature, sorts out the impact of online evaluation and AI recommendation link information of network homogenization products under AI technology screening on consumer product demand. Combining with the characteristics of the current experience economy era introduces consumer experience value, and based on stimulus–organism–response (S‐O‐R) theory, constructs a conceptual model of this study and proposes corresponding hypotheses, analysing the relationship between AI recommendation, experiential value, and product demand for homogeneous products. The empirical research mainly adopts the method of questionnaire survey, and the variable measurement draws on previous mature scales to redesign the measurement scale suitable for the actual research in this article. This survey ultimately distributed and collected 207 valid questionnaires and used SPSS software to conduct reliability and validity tests, factor analysis and regression analysis on the collected data. Through empirical analysis, it is found that online evaluation, AI recommendation information and experiential value of homogeneous products have a significant positive impact on product demand. Experience value plays a partial mediating role in the impact of online evaluation of homogeneous products on product demand and a complete mediating role in the impact of AI recommendation information of homogeneous products on product demand. Based on the above conclusions, this article proposes countermeasures and suggestions for the three main entities of e‐commerce platforms, merchants and consumers. This study theoretically enriches and improves marketing theory, expanding the research perspective of S‐O‐R theory. In practice, providing suggestions for different entities is conducive to achieving mutual benefit and win–win situation among the platform, merchants and consumers and assisting in building a harmonious consumption environment.
