From designer to curator: cognitive and creative trade-offs in GenAI-assisted design

Abstract This study investigates the impact of generative artificial intelligence (GenAI) on creative workflow in digital textile design. Thirty-four undergraduate students completed matched pattern design tasks using both conventional vector-based tools and GenAI-supported workflows within Adobe Illustrator. A within-subject experimental design was used to compare the two approaches. Paired comparisons showed that GenAI significantly reduced perceived task difficulty and total workload and increased procedural efficiency. However, these gains accompanied by lower editability and weaker articulation of personal style, along with lower ratings of creativity, aesthetic value, satisfaction, and goal fulfillment. Idea generation felt easier with GenAI, but the breadth of distinct ideas did not increase, suggesting stylistic convergence rather than divergent exploration. Qualitative data revealed a redistribution of cognitive effort, as automation eased technical operations but shifted focus to prompt formulation, weakening expressive control. This reflects GenAI’s dual effect of enhancing procedural fluency while diminishing authorship. For effective integration into education, this study proposes structuring AI-integrated design into an exploration, refinement, and reflection phase, accompanied by assessment that documents prompt, decision histories, and human re-authoring of AI results.