[目的/意义] 分析大模型在知识管理领域的应用场景和挑战，为相关领域的研究和实践提供参考和借鉴，促进大模型在知识管理领域更加深入的应用，提高知识管理工具的使用体验。[方法/过程] 通过跟踪软硬件厂商、商业化产品、开源项目、学术研究和客户的实际使用体验等多方面的动态，总结和梳理人工智能大模型在知识管理领域的实际应用以及在应用过程中面临的问题与挑战。[结果/结论] 人工智能大模型已成为知识管理的有力工具，得到越来越多的实际应用，包括辅助撰写文档、自动生成文档摘要、使用自然语言检索信息、智能问答等。这些应用改变了传统知识管理的方式，使其更高效、智能化和用户友好。然而，大模型在知识管理领域的应用也面临着一些尚待解决的问题，如数据隐私保护、知识产权保护、知识污染、高成本、内容输出不稳定等。

[Purpose/Significance] By analyzing the application scenarios and challenges of large models in the field of knowledge management, this paper aims to provide reference and inspiration for research and practice in related fields, promote the deeper application of large models in the field of knowledge management, and improve the user experience of knowledge management tools. [Method/Process] By tracking the dynamics of software and hardware vendors, commercial products, open source projects, academic research, and actual customer experience, the practical application of large models in the field of knowledge management, and the problems and challenges faced in the process were summarized and sorted out. [Result/Conclusion] Large models have become a powerful tool for knowledge management and have more and more practical applications, including assisting in document writing, automatically generating document summaries, using natural language to retrieve information, intelligent question answering, etc. These applications have changed the way traditional knowledge management operates, making it more efficient, intelligent, and user-friendly. However, the application of large models in the field of knowledge management also faces some unresolved problems, such as data privacy protection, intellectual property rights protection, knowledge pollution, high costs, and unstable content output, which have yet to be solved.