Key points are not available for this paper at this time.
Artificial intelligence (AI) has shown strong potential to assist product design, yet interaction modes and evaluation methods in human-AI co-creation remained unclear. This study systematically reviewed 50 empirical studies to: (1) categorize AI-supported design tools and their collaboration modes with designers; (2) analyze the design phases and domains supported by AI-supported design tools; and (3) synthesize assessment metrics for evaluating co-creation effectiveness. The review identified three interaction modes: human-centric, copilot, and AI-centric. It also showed that about 80% of studies focused on early ideation phases, while only 30% addressed evaluation and optimization. Assessment frameworks primarily targeted creative outcomes, system efficacy, and collaborative experiences. By mapping current research status and revealing moderation patterns among design phases, interaction modes, and user experience, this review provided actionable guidelines for designing future AI-assisted systems. Research findings highlighted AI’s potential to augment human creativity and provided support for the development of more effective, trustworthy co-creative AI-supported design tools.
Zhang et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: