To achieve the objective of sharing massive Internet of Things (IoT) healthcare data and enhance the efficiency and consistency of shared data, research on the sharing method for such vast datasets has been conducted using artificial intelligence technology. Initially, a distributed storage table is established to manage and store extensive IoT healthcare data. Subsequently, the heterogeneity of this data is analyzed based on the distinct distributions and characteristics of regional healthcare data. Building on this analysis, artificial intelligence technology is employed to virtualize the information data, streamlining the data access steps during the sharing process. Finally, a data-sharing model is designed so that once the requester passes authentication, the virtualized data is transmitted to them, enabling data sharing. Experimental results clearly demonstrate the high performance of this method in data sharing, which can share raw data with minimal loss and offers efficient sharing capabilities.