Comparing conventional and AI-aided approaches to architectural visuals: a pedagogical evaluation

The rise of AI in architectural design is changing traditional workflows, especially in tasks related to visualization and the refinement of incomplete architectural visuals. This chapter presents a comparative study between conventional digital editing methods and AI-aided completion tools within the context of architectural education. The aim is to understand how the integration of AI tools influences the process and its outcomes, specifically in terms of efficiency, accuracy, and usability for the production of architectural visuals. The research involves two groups of students completing the same tasks under identical constraints and objectives. The first group manually edits and completes architectural visuals using conventional Photoshop editing tools. The second group utilizes Photoshop Generative Fill tool that automates parts of the image completion process using AI-driven algorithms that generate detailed and contextually refined outputs. A reflexive thematic analysis-driven evaluation framework is employed to assess each group’s results, emphasizing qualitative insights while incorporating quantitative user ratings for complementary analysis. This comparative study explores how these tools impact students’ learning, creative decision-making, and ability to tackle complex real-world design challenges. By examining the outcomes of this pedagogical experiment, the study contributes to ongoing discussions about the role of AI in architectural education and practice.