Rethinking Inclusive Design in Higher Education: Integrating Generative AI and UDL Practices Through the UDL-AI-TPACK Model

Universal Design for Learning (UDL) offers a flexible and inclusive framework for designing learning environ-ments that address learner variability. While widely discussed in K – 12 settings, UDL remains underused in higher education, partly due to limited faculty training and the perceived complexity of its implementation. This chapter explores the potential of generative Artificial Intelligence (AI) as a catalyst for UDL adoption in universi-ty teaching and faculty development. Drawing from a training experience with pre-service schoolteachers – where AI tools were used to support in-clusive lesson planning – we propose a model for extending such practices to professors in higher education. The integration of UDL principles, AI literacy, and the TPACK framework can foster reflective and accessible course design among university faculty, resulting in what we will define as UDL-AI-TPACK model. Generative AI is examined not as a replacement for pedagogical intention, but as a design companion that prompts inclusive thinking and adaptive planning. The chapter discusses the theoretical underpinnings of this integration, presents insights from the initial case study, and outlines strategies for using AI to scaffold UDL-oriented faculty training. In doing so, it contributes to reimagining digital transformation in higher education through a lens of equity, flexibility, and pedagogical depth.