As generative artificial intelligence advances, Large Language Models (LLMs) are being explored for automated graphical user interface (GUI) design. This study investigates the usability and adaptability of LLM-generated interfaces by analysing their ability to meet diverse user needs. The experiments included utilization of three state-of-the-art models from January 2025 (OpenAI GPT o3-mini-high, DeepSeek R1, and Anthropic Claude 3.5 Sonnet) generating mockups for three interface types: a chat system, a technical team panel, and a manager dashboard. Expert evaluations revealed that while LLMs are effective at creating structured layouts, they face challenges in meeting accessibility standards and providing interactive functionality. Further testing showed that LLMs could partially tailor interfaces for different user personas but lacked deeper contextual understanding. The results suggest that while LLMs are promising tools for early-stage UI prototyping, human intervention remains critical to ensure usability, accessibility, and user satisfaction.

翻译：随着生成式人工智能的发展，大型语言模型（LLMs）正被探索用于自动化图形用户界面（GUI）设计。本研究通过分析LLM生成界面满足多样化用户需求的能力，探讨其可用性与适应性。实验采用了2025年1月发布的三种前沿模型（OpenAI GPT o3-mini-high、DeepSeek R1和Anthropic Claude 3.5 Sonnet），针对三种界面类型生成设计原型：聊天系统、技术团队面板和管理者仪表盘。专家评估表明，虽然LLMs能有效创建结构化布局，但在满足无障碍访问标准和提供交互功能方面仍面临挑战。进一步测试显示，LLMs能够针对不同用户角色部分定制界面，但缺乏更深层次的上下文理解。结果表明，尽管LLMs是早期用户界面原型设计的有前景的工具，但为确保可用性、无障碍访问和用户满意度，人工干预仍然至关重要。