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This research delves into the cutting-edge integration of large language models (LLMs)into a user-centric interface, aiming to enhance qualitative interview research through the development of the AI-powered tool called Gen-AI Interviews. Prioritizing user-friendliness and efficiency, the study employs Design Thinking principles across iterative design stages, from empathizing to the testing of low-, mid-, and high-fidelity prototypes. Central to the project is a focus on user-centricity, simplicity, and the strategic incorporation of technology, with each design iteration refined through expert and user feedback. The Gen-AI Interviews platform adeptly demonstrates the power of LLMs in automating tasks like data analysis and management while preserving ease of use and user engagement. The platform’s efficacy and usability are validated through tools such as the NASATask Load Index. Key outcomes of this study include the effective utilization of AI to enhance qualitative research efficiency and ensure data security and user engagement. This research not only contributes significantly to the field of AI-enhanced user interfaces but also lays a foundational framework for future advancements that emphasize user experience in AI-driven technologies, positioning the Gen-AI Interviews platform as a transformative tool for researchers and setting an example for AI integration in professional tools and systems.