Since Generative AI (GenAI) has introduced in 2022, it has transformed teaching and learning in higher education in diverse aspects. Students are increasingly using diverse GenAI tools to understand complex theories, generate ideas, draft work, create presentations with scripts, and obtain instant solutions to assignments. This dramatic shift in learning styles raises concerns on how to integrate this emerging technology while ensuring students are trained as problem-solvers who can effectively utilize AI without over-relying on it. As students’ needs vary across disciplines, it is critical to address this potential disparity in the ways in which different student groups learn, understand, and apply GenAI may differ, including in interdisciplinary courses. Toward this goal, this paper reviews the literature on GenAI in higher education, highlighting the lack of research addressing the differences among student groups. To bridge this gap, we propose the GAITE project, which aims to identify and address the unique needs of these groups through surveys and tailored solutions.