BEIJING, CHINA / RankWire.AI / – Artificial intelligence is increasingly being incorporated into traditional Chinese medicine education, research, and clinical support across China. Beijing University of Chinese Medicine has created a specialized large model centered on extensive TCM knowledge and learning materials. The Xinhuo TCM system includes classical texts, medical theories, herbal information, prescriptions, and teaching resources. Its developers launched the initial version in 2025 and expanded the platform during 2026.
According to the university, Xinhuo TCM now functions as a 70-billion-parameter system built on major Chinese artificial intelligence platforms. The model was designed to support learning, teaching, research, administration, and international communication related to traditional Chinese medicine. Students can inquire about herbal combinations and receive explanations about formulas and their foundational principles. Additionally, the university has developed an intelligent robot that demonstrates traditional massage techniques for practical training.
AI’s growing role in traditional Chinese medicine in China also extends to medical knowledge management and clinical support tools. Digital systems are capable of organizing historical medical literature and structuring information from experienced practitioners for educational and research purposes. Researchers are exploring artificial intelligence for diagnostic data, pre-consultation systems, and other decision-support applications. These initiatives reflect a broader effort to link traditional medical knowledge with modern data and computing technologies.
China advances digital infrastructure to support TCM development
China has incorporated artificial intelligence into its national traditional medicine development framework for the period from 2026 to 2030. The National Administration of Traditional Chinese Medicine and the National Development and Reform Commission issued the plan in July. It emphasizes the creation of high-quality artificial intelligence datasets specifically tailored for the traditional Chinese medicine sector. The plan also promotes digital infrastructure, smart traditional medicine hospitals, and intelligent diagnostic assistance at primary healthcare facilities.
The national strategy emphasizes data governance alongside the expansion of artificial intelligence tools within the traditional medicine system. It advocates for enhanced data classification, protection, and compliant circulation across healthcare, research, and related digital services. The authorities also aim to increase the adoption of standardized intelligent equipment and digital technologies in traditional Chinese medicine, covering clinical services, education, scientific research, and the management of traditional medicine information.
AI technologies transition from educational tools to clinical applications
Research released in 2026 has also explored the performance of large language models within traditional Chinese medicine healthcare environments. One study assessed an AI pre-consultation system at a tertiary traditional medicine hospital and found initial acceptance among physicians. Medical professionals responded more favorably to its ability to gather information prior to consultations than to some decision-support functions. Researchers noted remaining challenges related to complaint capture, workflow integration, documentation requirements, and accessibility for older patients.
Recent advancements demonstrate AI’s expanding presence across various segments of China’s traditional Chinese medicine system. Xinhuo TCM has obtained national registration for generative AI services, integrating the specialized model into China’s regulatory framework for public AI services. Current applications include education, research, knowledge management, hospital workflows, and auxiliary diagnostic tools. China’s 2026 to 2030 TCM development plan now officially incorporates artificial intelligence datasets and digital medical infrastructure as key components of the sector’s growth.