The rapid advancement and application of AI in design education are fully evidenced at the start of the new 2026/27 academic year. Indeed students, tutors and faculty now take AI tools, such as ChatGPT and Midjourney, for granted in teaching and learning design echoing that of professional production. But while AI tools help students spend less time on repetitive tasks like drafting, organising research data or checking design quality before review, they raise as many questions as they answer. For example, from a pedagogic perspective, what exactly are students learning when using AI? And so, when to use AI for ideation, for project development or analysis? And how to document and present an AI-assisted process in reviews and portfolios that looks genuine and authentic? That is, students competency versus tool competency. Also, what evidence of student observational skills, material and technical knowledge and personal judgement? And proof that they not only can prompt effectively, curate, edit, and direct outputs, but also use AI tools critically understanding their limitations? AI-immersed design education, then, highlights the new relationship between student, tool and faculty. The dynamic has changed: where does knowledge and authority reside, and what is being evaluated and valued?
