The continuous development and progress of biotechnology and information technology provides data for pharmaceutical research and application. It is difficult to fully utilize large-scale data with simple statistical analysis methods. In order to improve data utilization, pharmaceutical research must be promoted using advanced information analysis. Artificial intelligence has experienced half a century of development since its inception and has been successfully applied to many industrial and technological fields. Recently, breakthroughs in machine learning represented by deep learning have made artificial intelligence one of the most popular research directions. Artificial intelligence algorithms use different types of data based on various strategies to do multiple tasks such as search and discrimination, and are suitable for solving massive data analysis problems faced in network pharmacological research. This chapter briefly introduces artificial intelligence algorithms and their applications in network pharmacology research, and provides references for researchers to better understand and apply artificial intelligence.