Impact of generative AI on studio-based learning in architectural education: insights from a case study in Cairo University

Purpose This study investigates the impact of stage-specific integration of Generative AI (GenAI) on learning processes in studio-based architectural education, assessed through design quality, student performance, and design productivity. Design/methodology/approach The research reviewed literature on traditional architectural design processes, theories of design education, and the impact of AI-integrated learning. Subsequently, a pilot questionnaire was administered to undergraduate architecture students across all four levels to identify gaps in the use of AI tools within design studios. This was followed by a supervised senior-level project at the Faculty of Engineering, Cairo University (CUFE), comparing performance of an AI-assisted group with a conventional group. Additionally, interviews with the participants were conducted to triangulate quantitative findings. Findings The findings indicate the AI-assisted group demonstrated a 14% improvement in creativity, design form, and visualization, and deliverable quantity, 14% higher productivity compared to the conventional group, with strong gains among lower-performing students. The results suggest that structured stage-specific AI integration can enhance students' performance particularly during key stages such as form generation and façade design. Practical implications The study proposes a recommended framework connecting design stages with GenAI outputs, offering practical guidance for educators on when and how AI tools can be integrated into architectural design studios. Originality/value In this AI paradigm shift, this study provides context-specific empirical evidence on stage-oriented GenAI integration in architectural education, employing a multi-layered methodological structure within a developing-country context.