A Framework for enhancing UI Consistency Through Artificial Intelligence

Objective: This paper proposes a framework to help UI designer utilize AI for maintaining visual consistency in user interface (UI) design.<br/>Background: UI consistency plays a critical role in user experience by improving predictability, usability, and visual coherence across digital products. Traditional methods for ensuring consistency (heuristic evaluation, cognitive walkthrough, formal usability, pluralistic walkthrough, feature inspection, consistency inspection, and standards inspection) are widely used despite being time-consuming and resource-intensive. With the rise of AI in design, there is growing interest in how these technologies can support consistency. However, AI used in past researches remains unavailable to the majority of designers.<br/>Method: The framework was created through pairing AI available as plugins in Figma with a three-part taxonomy (physical, communicational, conceptual) inside an industry-standard design environment. To evaluate the framework, a set user interfaces were designed following our framework is compared with three other sets with varying inconsistencies. Afterwards, forty UI/UX designers were asked to finish a set of tasks to probe for the user experience across three key areas: task completion time, clarity rate, and satisfaction.<br/>Results: Results revealed that our proposed AI-assisted framework improves core UX outcomes by enabling designers to maintain higher consistency using accessible AI tools integrated into standard workflows.<br/>Conclusion: The framework successfully addresses the gap between AI application in research and design practice by pairing accessible, Figma-integrated tools into a three-part consistency framework. By combining AI-supported checks with manual reviews, teams can cut post-design effort while maintaining review depth and reliability. Future development should focus on expanding the sample size for better validity, as well as updating AI technology as needed.<br/>Application: This framework can be adopted by UI designers seeking to utilize AI for UI consistency. It is especially useful for product teams during post-design audits.

Authors

Publication Details

Journal
Journal of the Ergonomics Society of Korea
Published
2025-12-31
DOI
https://doi.org/10.5143/jesk.2025.44.6.747
Primary Topic
Usability and User Interface Design
Type
article
Field-Weighted Citation Impact
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article

A Framework for enhancing UI Consistency Through Artificial Intelligence

Y. Pan, Chi Nhan Huynh
Journal of the Ergonomics Society of Korea
Usability and User Interface Design
article

A Framework for enhancing UI Consistency Through Artificial Intelligence

Y. Pan, Chi Nhan Huynh
article en

Abstract

Objective: This paper proposes a framework to help UI designer utilize AI for maintaining visual consistency in user interface (UI) design.<br/>Background: UI consistency plays a critical role in user experience by improving predictability, usability, and visual coherence across digital products. Traditional methods for ensuring consistency (heuristic evaluation, cognitive walkthrough, formal usability, pluralistic walkthrough, feature inspection, consistency inspection, and standards inspection) are widely used despite being time-consuming and resource-intensive. With the rise of AI in design, there is growing interest in how these technologies can support consistency. However, AI used in past researches remains unavailable to the majority of designers.<br/>Method: The framework was created through pairing AI available as plugins in Figma with a three-part taxonomy (physical, communicational, conceptual) inside an industry-standard design environment. To evaluate the framework, a set user interfaces were designed following our framework is compared with three other sets with varying inconsistencies. Afterwards, forty UI/UX designers were asked to finish a set of tasks to probe for the user experience across three key areas: task completion time, clarity rate, and satisfaction.<br/>Results: Results revealed that our proposed AI-assisted framework improves core UX outcomes by enabling designers to maintain higher consistency using accessible AI tools integrated into standard workflows.<br/>Conclusion: The framework successfully addresses the gap between AI application in research and design practice by pairing accessible, Figma-integrated tools into a three-part consistency framework. By combining AI-supported checks with manual reviews, teams can cut post-design effort while maintaining review depth and reliability. Future development should focus on expanding the sample size for better validity, as well as updating AI technology as needed.<br/>Application: This framework can be adopted by UI designers seeking to utilize AI for UI consistency. It is especially useful for product teams during post-design audits.

Journal of the Ergonomics Society of KoreaVol. 44(6)
Openalex Percentile: Top 20%
Usability and User Interface Design
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A Framework for enhancing UI Consistency Through Artificial Intelligence — Y. Pan, Chi Nhan Huynh · Journal of the Ergonomics Society of Korea (2025) | TGRS Research Map | TGRS