Systematic Literature Review on the Impact of Artificial Intelligence on UI/UX Design

Abstract

Artificial Intelligence (AI) is increasingly used in User Interface (UI) and User Experience (UX) design to support automation, personalization, usability evaluation, design ideation, and decision-making, yet existing studies remain fragmented across techniques, tools, and applications. This study presents a Systematic Literature Review (SLR), reported following PRISMA, of AI’s impact on UI/UX design using studies from Scopus and Google Scholar (2020–2025). From 211 identified records, 82 approved records corresponding to 79 unique studies were analyzed. Machine learning, deep learning, generative AI, natural language processing, explainable AI, and large language models are the most common techniques, applied mainly to usability evaluation, personalization, interface generation, recommendation, code generation, design ideation, and user behavior analysis. Reported impacts concern usability, efficiency, creativity, satisfaction, personalization, trust, and accessibility, while limitations persist in adoption, evaluation, transparency, designer control, privacy, ethics, and bias. Beyond mapping the field, this study integrates the findings into a three-layer conceptual framework linking AI capabilities, design functions, and human-centered outcomes under moderating conditions of responsible use, and derives testable propositions. The results suggest that AI can improve UI/UX design workflows but should support rather than replace human designers.