Design-System-Aware Development with AI: Evaluating Productivity and Design Consistency

• URL: http://arxiv.org/abs/2607.13156v1
• Date: Tue, 14 Jul 2026 18:06:29 GMT
• Title: Design-System-Aware Development with AI: Evaluating Productivity and Design Consistency
• Abstract summary: This paper reports a controlled experiment conducted at a large Brazilian enterprise that compares manual development, DS-only development, and DS-aware AI-assisted development.<n>Results show that AI assistance significantly reduced time-to-delivery, increased task completeness, and decreased variability.<n>These findings provide empirical evidence that DS-aware AI tools can significantly accelerate development, improve design fidelity, and yield practical benefits for industrial front-end performance.
• Score: 2.325469439198971
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Design Systems (DS) help standardize front-end development, yet developers still face challenges when translating high-fidelity mockups into consistent, production-ready interfaces. Although AI-assisted tools have emerged as a potential solution, empirical evidence on their effectiveness within DS-centered workflows remains limited. This paper reports a controlled experiment conducted at a large Brazilian enterprise that compares manual development, DS-only development, and DS-aware AI-assisted development across Angular, iOS, and Android stacks. Results from two experimental cycles show that AI assistance significantly reduced time-to-delivery (by 46.7% to 69.4%), increased task completeness, and decreased performance variability. Analysis of break patterns further suggests reduced workflow friction and smoother task execution. These findings provide empirical evidence that DS-aware AI tools can significantly accelerate development, improve design fidelity, and yield practical benefits for industrial front-end workflows.

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