What question did this study set out to answer?

The framework aims to assist UI designers in using AI to maintain visual consistency in design.

March 25, 2026

A Framework for enhancing UI Consistency Through Artificial Intelligence

Key Points

The framework aims to assist UI designers in using AI to maintain visual consistency in design.
Developed a framework pairing AI plugins in Figma with a three-part taxonomy.
Evaluated design consistency using a comparison of user interfaces created with the framework and three inconsistent sets.
Conducted user experience assessments with 40 UI/UX designers focusing on task completion time, clarity rate, and satisfaction.
The AI-assisted framework improved task completion rates and overall user satisfaction.
Designers experienced higher consistency in their work using the framework.
The approach integrated AI tools into standard workflows effectively reduced post-design efforts.

Abstract

Objective: This paper proposes a framework to help UI designer utilize AI for maintaining visual consistency in user interface (UI) design.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.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.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.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.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.

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