Purpose/Significance To explore the governance path of AI-ready data in the medical field, and to provide references for the construction of AI-ready data in China. Method/Process By using methods such as case analysis and content analysis, based on information such as the strategic planning, research projects and funded scientific projects of the U.S. National Institutes of Health (NIH), the experience of AI-ready data governance is analyzed from the perspectives of practical measures, promotion mechanisms and implementation paths. Result/Conclusion AI-ready data governance in the medical field is a system engineering that encompasses standards, tools, ethics, and capabilities. It is necessary to integrate multiple elements such as biomedical research, AI development, and application scenarios for coordinated advancement.