Evaluating the impact of AIGC-Supported design ideation on Designers’ cognitive load and creativity

Although AI-assisted design shows promise for improving efficiency and ideation, its effects on cognitive load and creativity across different design stages remain unclear. This study examines the integration of AI-generated content (AIGC) into a two-stage workflow, focusing on ideation and subsequent concept development. In a controlled experiment, participants completed the same design challenge under three assistance modes: AI-supported collaboration, designer-to-designer collaboration, and image-stimulus support. Cognitive load was assessed with NASA-TLX, creativity with the Creative Product Semantic Scale (CPSS), and physiological responses with heart rate variability (HRV) and eye tracking (ET). During ideation, AIGC support selectively reduced perceived mental demand compared to designer-only collaboration, and CPSS ratings for novelty and resolution trended higher. ET further indicated shorter scanpaths under AI, suggesting leaner visual search. In the development phase, differences were more modest: curated image stimuli and AIGC both reduced workload relative to the control, with image stimuli supporting resolution and AIGC enhancing novelty and elaboration. Taken together, these results suggest that under controlled conditions, AIGC is most effective in the divergent ideation phase, while in convergent development, curated and generative visual stimuli provide complementary support.