With the rapid development of digital technology, the design and application of human-computer interaction systems are receiving increasing attention. Based on the design principles of generative artificial intelligence, this article focused on how to apply this technology to digital media through in-depth exploration and experimentation. This article aimed to obtain user behavior and response patterns from multidimensional data, and based on this, learn and optimize interaction models to achieve more personalized interaction effects. This article provided a detailed comparison and analysis of various existing interactive systems, and evaluated their performance and user experience in practical use. Therefore, this article started from the perspective of human-computer interaction and improved the performance and efficiency of human-computer interaction by simulating the perception and cognitive processes of humans. In addition, a study was also conducted on different application scenarios such as intelligent education, e-commerce, and online customer service. The first attempt time for user 9 was the minimum, reaching 105 s, and then continued to shorten until it remained at 65 s. The research results of this article can provide new ideas and methods for the intelligent human-computer interaction research of digital media.