This paper investigates the application of Artificial Intelligence-Generated Content in the generation of individualized learning content for undergraduates and proposes a method for personalized learning content generation based on the Transformer model. It explains in detail how, through literature review, model selection and construction, algorithm design and optimization, and model performance evaluation, AIGC technology can be used for realizing automatic generation and personalized customization of learning content. Analysis of confirmed cases has shown that this technology will significantly enhance the efficiency of students’ learning and performance, offer diversified and balanced learning content, and so on. It has enormous application prospects in online education platforms intelligent tutoring, and adaptive learning systems. This technology can provide students with individualized study content to suit their needs, optimizing studying experience and improving learning effects. Theoretical and practical support from this research outcome will be given to popularize further and apply personalized learning content generation technology.