Against the backdrop of rapid global AI iteration and deep industry integration, universities, as key carriers of AI basic research, have their technology transfer efficiency directly affecting the alignment between innovation and industrial chains. Technological powers such as the US, Europe, Japan, and South Korea, leveraging well-established systems, professional tech transfer offices, in-depth industry-university-research collaboration, and resource support, have developed a transformation model adapted to AI’s asset-light, fast iteration, and scenario-specific features, significantly improving industrialization rates. This paper takes leading universities such as Stanford University as research subjects, systematically reviewing their practical experiences in institutional design, organizational operations, and other aspects, to provide reference for Chinese universities in addressing pain points in AI technology transfer and building an efficient, compliant ecosystem for innovation transformation.