Background: Current evidence dissemination methods fall short of meeting clinical nurses’ needs, hindering the implementation of evidence-based nursing practice. Large language models (LLMs), with their advanced natural language processing capabilities, offer potential as innovative tools to facilitate evidence dissemination. However, general-purpose LLMs typically lack domain-specific knowledge, are insufficient to support effective evidence dissemination in clinical contexts. It is essential to develop artificial intelligence tools tailored to nurses’ needs and preferences to enhance evidence dissemination. Objective: The aim of this study is to identify the challenges and barriers clinical nurses face in disseminating evidence, examine their perspectives on the use of existing LLMs to support evidence dissemination, and explore their needs and preferences regarding an LLM-based nursing evidence question-answering system. Methods: This qualitative study used a combined method of focus group discussions and the nominal group technique (NGT). Using purposive sampling, nurses with diverse specialties, professional titles, and years of experience were recruited, resulting in a total of 22 clinical nurses who completed the entire study. A total of 2 focus group discussions were conducted online via Tencent Meeting between November and December 2024 to explore the challenges and barriers nurses face in disseminating evidence, as well as their perspectives on using existing LLMs to support evidence dissemination. The data were analyzed using qualitative content analysis following the approach of Graneheim and Lundman. Subsequently, the NGT was used between March and April 2025 to identify nurses’ needs and preferences for the system to be developed. To overcome geographical constraints and participants’ busy schedules, the NGT was conducted entirely online, using online questionnaires and WeChat groups. Overall, 2 rounds of voting were conducted to determine the priority ranking of the functionalities. Results: The focus group yielded 3 main themes and 7 subthemes. Three main themes were identified as (1) pathways for evidence dissemination among nurses, (2) barriers that hinder the effective dissemination of evidence, and (3) advantages and limitations of using LLMs to support evidence dissemination. The limitations of current LLMs served as the foundation for nurses’ subsequent reflections in the nominal group discussions on the desired functions of a newly developed LLM. The NGT sessions ultimately identified 9 desired functions. After prioritization, the top 3 ranked functions were evidence-based, high-quality question-answering, evidence source provision, and personalized evidence recommendation. Conclusions: The current evidence dissemination process faces multiple barriers. LLMs hold promise as innovative tools to support evidence dissemination, but require further refinement. Clinical nurses have identified key functional needs, guiding the development of LLMs specifically tailored to clinical nursing practice.