Generative AI-enabled chatbots for user-centred design: a state-of-the-art review
Tianyu Zhou, Ying Liu, Maneesh Kumar, Sibao Wang · Journal of Engineering Design · 2026
With the rapid advance of generative artificial intelligence (GenAI), particularly large language models, user-centred design (UCD) is transforming from static, fragmented design approaches to dynamic, interactive, and collaborative ones. Compared with traditional requirements elicitation and design support methods, GenAI-enabled chatbots provide scalable, adaptive, and context-aware support throughout the design process. This research conducts a review of relevant studies published between 2015 and 2025. It proposes an analytical framework including cognitive augmentation, collaborative facilitation, and workflow integration to explain how GenAI chatbots empower UCD across problem framing and user research, idea generation, prototype development, and iterative optimisation. The findings indicate that GenAI chatbots are evolving from conversational agents into interactive collaborators, expanding designers’ capabilities in information processing, ideation, and iterative refinement. This review also highlights that such a transformation has raised challenges, including the allocation of human–AI roles, limitations in domain-specific knowledge integration, the lack of robust evaluation frameworks, and concerns around explainability, ethics, and trustworthiness. Considering these concerns, this study identifies future research directions, including hybrid human–AI collaboration models, domain-specific and multimodal knowledge support, and systematic evaluation and governance frameworks. This research not only deepens the understanding of human–AI collaborative generative intelligent design but also demonstrates the transformative role of GenAI chatbots in advancing the next generation of user-centred design.