How generative AI is reshaping UI/UX design workflows: A systematic review
Open Access
Article
Conference Proceedings
Authors: Tarika Kumar, Xinyi Tu, Matteo Zallio
Abstract: As GenAI technologies such as large language models, diffusion models, and multimodal generative systems increasingly permeate design workflows, their implications for creativity, methodology, ethics, and collaboration demand critical scholarly attention. This paper presents a systematic literature review of generative artificial intelligence (GenAI) in user interface (UI) and user experience (UX) design, drawing on fifty peer-reviewed and preprint articles published between 2020 and 2025. The review is structured around five research questions, addressing: (1) the stages of the UI/UX design process where GenAI tools are most actively applied, (2) the methodological approaches used to evaluate their integration, (3) the ethical considerations arising from their use, (4) models of human-AI collaboration in design practice, and (5) the research gaps that shape the future trajectory of this field. Findings indicate that while GenAI tools are widely adopted in prototyping and visual asset generation, their use in early-stage conceptualization and UX evaluation remains limited. The literature also reveals methodological fragmentation and a lack of standardized evaluation frameworks. Ethical concerns surrounding bias, transparency, and privacy are underexplored, and few studies provide robust models for collaborative work between humans and AI. This review identifies the need for longitudinal research, structured participatory frameworks, and ethically grounded design methodologies. The paper contributes a comprehensive synthesis of current knowledge and outlines directions for future inquiry at the intersection of generative AI and human-computer interaction.
Keywords: Generative AI, Human-AI Collaboration, UI/UX Design, Design Process, Creative AI, Systematic Literature Review
DOI: 10.54941/ahfe1007056
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