<p>Universal design for learning (UDL) is a framework that promotes accessibility in education to accommodate the widest possible range of learners. Among UDL’s core principles, this study focuses on providing multiple means of representation, specifically through the use of summaries as an alternative way to convey the content of video lectures. We investigate the effectiveness of current AI models in generating text-based abstractive summaries as a complementary method for representing recorded lecture content. By comparing students’ perceptions of AI-generated summaries versus human-generated ones, our findings indicate that current AI models are capable of producing coherent and valuable lecture summaries. From the students’ perspective, these AI-generated summaries are seen as a beneficial addition to their learning materials. However, our study also highlights the need for educators to curate these summaries to ensure their quality. Through a quality of experience analysis, the factors shaping the learning experience and the extent of control available to learning facilitators were identified. Further research is needed to explore how lecture content influences student perceptions and to optimise AI-generated summaries for educational use.</p>