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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65736
Volume:
10 |
6 |
Jun 2026
Pages:
1-19
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Technology
University of Mumbai
Department of Computer Science and Technology
University of Mumbai
In today’s era of rapid technological advancement, the discipline of User Interface (UI) and User Experience (UX) design has undergone a profound transformation, driven largely by the rise of Artificial Intelligence (AI). This study explores the impact of AI on the practice of UI/UX development—examining how generative models, machine learning, and intelligent design tooling are reshaping the way digital products are conceived, prototyped, tested, and shipped. One of the central aims of this study is to analyze the influence of emerging AI technologies—such as generative UI engines, large language models (LLMs), AI-assisted design tools (Figma AI, Uizard, Galileo AI, Adobe Firefly, and Sensei), automated user-research platforms, and adaptive personalization systems—on the modern design workflow. The findings of this study suggest that the field of UI/UX design, like any other technology-adjacent discipline, is evolving at an accelerating pace, and that designers, product teams, and organizations must adapt to this evolution in order to remain competitive and to harness these tools for sustainable, human-centered outcomes. This research analyzes global trends in the AI-augmented design industry to understand adoption, usage, productivity impact, cost implications, and the changing scope of the designer’s role. A detailed SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis of AI in UI/UX development is performed. Because digital interfaces are now the primary medium through which billions of people interact with products and services, the quality of those experiences—and the speed at which they can be created—has become a decisive competitive factor for organizations of every size. A detailed analysis of the AI-in-design landscape is conducted using a range of secondary data sources, including industry reports, design-tool documentation, peer-reviewed HCI literature, blogs, and interactions with practitioners and organizations active in the field. Trustworthy and credible articles are also referenced as sources of authentic information. The results reveal that AI is being adopted most rapidly at the divergent, generative stages of the design process—ideation, wireframing, content generation, and rapid prototyping—while final visual craft, strategy, and accessibility judgment remain firmly human-led.
KEYWORDS
The practice of UI/UX development has evolved significantly, driven by emerging AI technologies, a growing market for digital experiences, and increasingly iterative, Agile-aligned design methodologies. This research has analyzed the field’s growth trends, tooling landscape, and challenges, providing a comprehensive overview of its current state and future potential. The study concludes by laying a foundation for further exploration across several critical areas: AI & Automation: AI-driven ideation, generative UI, content creation, and design-to-code automation are compressing the early stages of the design process and raising baseline output expectations.Human-Centered Judgment: Strategy, empathy, aesthetic craft, and ethical decision-making remain firmly human responsibilities, with AI serving as an assistant rather than an author.Accessibility & Inclusion: AI offers powerful tools to advance accessible design, but automated checks must be paired with human evaluation and testing with real users.Governance & Ethics: Responsible adoption requires clear policies on data privacy, intellectual property, bias mitigation, and quality assurance.The Evolving Designer: The designer’s role is shifting toward curation, systems thinking, and direction—making AI a force multiplier for those who pair it with strong judgment.
[1] J. Nielsen and R. Budiu, “AI and the Future of UX Work,” Nielsen Norman Group, 2023–2024. [2] McKinsey & Company, “The Economic Potential of Generative AI: The Next Productivity Frontier,” McKinsey Global Institute, 2023. [3] Figma, “State of Design / AI in the Design Process,” Figma Annual Report, 2024. [4] K. Todi, et al., “Machine Learning for User Interface Design and Optimization,” ACM Transactions on Computer-Human Interaction, 2021. [5] A. Swearngin and Y. Li, “Modeling Mobile Interface Tappability Using Crowdsourcing and Deep Learning,” Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, 2019. [6] Adobe, “Adobe Firefly and Sensei: Generative AI for Creative Workflows,” Adobe Research & Product Documentation, 2023–2024. [7] Interaction Design Foundation, “Artificial Intelligence in UX Design,” IxDF Literature, 2023. [8] WebAIM, “The WebAIM Million: An Annual Accessibility Analysis of the Top 1,000,000 Home Pages,” Utah State University, 2024. [9] W3C, “Web Content Accessibility Guidelines (WCAG) 2.2,” World Wide Web Consortium, 2023. [10] Gartner, “Market Guide for Digital Design and Prototyping Tools,” Gartner Research, 2023.
Publication Date
6/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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