高校是国家科技创新体系的核心组成部分，其知识产权运营水平直接关系到智力成果向现实生产力的转化效率，对推动产业升级和经济高质量发展具有关键作用。经过多年实践，我国高校已探索形成内生驱动、外部联动、专业托管等多样化的知识产权运营模式，但“重数量轻质量、重研发轻市场、重形式轻实效、重保护轻预警”等深层次问题依然突出。在此背景下，研究中将借助人工智能技术的强大数据处理与智能分析能力，破解传统运营模式的瓶颈，为构建高效、精准、智能的新型运营体系提供参考路径。

Colleges and universities are a core component of the national scientific and technological innovation system. Their intellectual property (IP) operation capabilities are directly related to the efficiency of transforming intellectual achievements into practical productive forces, and play a crucial role in promoting industrial upgrading and high-quality economic development. After years of practice, Chinese colleges and universities have explored and formed diverse IP operation models such as endogenous drive, external linkage, and professional trusteeship. Problems like “dormant”patent achievements and low transformation efficiency persist, making it difficult to adapt to the increasingly large scale of patents and complex market demands. Against this backdrop, this study will leverage the powerful data processing and intelligent analysis capabilities of artificial intelligence (AI) technology to break through the bottlenecks of traditional operation models , provide a reference path for building an efficient, precise, and intelligent new operational system.