Generative AI as a cognitive support tool in early-stage design ideation: A human–AI co-ideation experiment

Abstract

Generative artificial intelligence is increasingly used in creative practice, but controlled evidence on its role in early-stage design ideation remains limited. This study examined whether a combined text-and-image AI-assisted workflow differed from human-only brainstorming in expert-rated ideation outputs, preliminary design refinement, and subjective task experience. A counterbalanced within-subjects experiment was conducted with 32 undergraduate design students, each of whom completed both conditions using the same design brief. Ideation outputs were evaluated by three expert raters across six task-specific analytic criteria, participant-matched concept sheets were assessed across five design attributes, and participants completed a task-specific post-task questionnaire after each condition. After Holm–Bonferroni correction within each outcome family, AI-assisted outputs received higher ratings for problem framing, mechanism, creator perspective, and evaluator perspective, whereas human-only outputs received higher ratings for innovation and proposed solution strategies. No statistically robust condition differences were found for the five design attributes. Participants reported higher ratings for perceived cognitive processing, self-rated ideation skills, and affective response in the AI-assisted condition. These findings indicate different profiles of evaluated ideation output rather than a uniform advantage for either condition. Perceived support in the AI-assisted workflow did not translate into a uniform advantage across originality-related ratings or into superior expert-rated preliminary design refinement.