The era of data supremacy: How can AI healthcare reconstruct the trillion-dollar health industry value chain?

5AI Overall, the release of the DeepseekR1 version in January 2025 has triggered a wave of low-cost, high-quality AI applications. Medical AI is seen as one of the most important and promising scenarios for AI applications and is highly valued by the market. According to wind data, the AI healthcare index (887738.WI) has increased by 55.24% since its low point in January. On one hand, in recent years, there have been frequent AI healthcare policies that have accelerated the industry's development with policy support. On the other hand, AI has shown significant results in reducing costs and increasing efficiency, leading to a stronger commercialization desire. Policies embracing AI applications in healthcare As a heavily regulated industry, the medical field benefits from policies that encourage and accelerate its development. Since 2019, there have been multiple favorable policies for AI healthcare. For example, in October 2019, the NMPA announced the establishment of a unit for standardizing medical equipment, including AI. In March 2021, further policies were introduced to promote high-quality development of medical equipment standardization. In July 2021, guidelines for the classification of AI medical software products were released. In July 2022, guidance on promoting innovation through AI applications was issued by six departments, including the Ministry of Science and Technology. In November 2024, various health agencies jointly released a reference guide for AI applications in healthcare, providing a clear direction and support for AI in the medical field. This guide lists 84 specific AI technologies to be applied in medical service management, primary public health services, health industry development, and medical education and research. This provides concrete guidance for the application of AI technologies in healthcare, facilitating their implementation and promotion. The guidance and support from policies will encourage more investment and innovation, driving the rapid development of AI technologies in healthcare. Rapid application of AI in various fields of healthcare AI technologies have been gradually applied in various aspects of healthcare, including medical imaging, diagnostic assistance, drug development, etc. For example, in medical imaging, AI has significantly improved diagnostic accuracy and efficiency, optimizing the image analysis process. In diagnostic assistance, AI analyzes patients' electronic health records and genomic data to provide personalized treatment recommendations, assisting doctors in precise surgical operations. In drug development, AI has shortened development cycles, reduced costs, and improved success rates. According to the XTALPI-P prospectus citing Frost & Sullivan data, under the influence of AI, the drug discovery process has been shortened by 50%. With policies and substantial benefits, the stock prices of AI healthcare companies have seen significant increases. Not only have domestic AI healthcare companies experienced sharp rises in stock prices, but overseas AI healthcare companies have also seen substantial increases, with validated performance. The rise in overseas AI healthcare stock prices reflects the favorable conditions for domestic AI healthcare companies. Validation of the commercial model of leading AI healthcare company Tempus Taking the example of the leading AI healthcare company in the US, Tempus (TEM.US). Tempus has become a global benchmark in precision medicine with its business model of "data + algorithms + applications." Tempus' platform consists of three main product lines: Genomics (genomic diagnostic tests), Data service (data services), and AI-relative application (AI application platform). According to the company, each of its businesses synergizes/integrates with others, enhancing the competitiveness of other businesses and highlighting the company's core value in the field of AI healthcare. The growth and success of Tempus from its establishment to its expansion can be attributed to its "traffic or data entry." The interaction between the database's size, the increase in data and service revenue, and the quality and quantity of genomic/diagnostic and algorithm tests form a flywheel effect. This effect drives the continuous growth of the company's data volume, making Tempus one of the world's largest clinical and molecular oncology databases. It connects with 65% of academic medical centers and 50% of oncologists in the US, holding 8.5 million clinical records, 1.2 million imaging records, and 250PB of multimodal data, establishing the company's core strengths. In November 2024, Tempus acquired genetic testing company Ambry Genetics, expanding its services to pediatric, rare diseases, immunology, reproductive health, and cardiology. Tempus has disclosed that it has partnerships with 19 of the top 20 pharmaceutical companies in terms of revenue ranking in 2023. Additionally, its collaboration with large healthcare companies continues to expand in 2025. The company's business model has been validated in the market, providing insights and inspiration for domestic AI healthcare enterprises.The total remaining contract value of the contract signed three years ago exceeds 900 million dollars, and is expected to be delivered in installments in the coming years.In Tempus' three product lines, the AI application product line achieved revenue of $5.5 million in 2023, accounting for 1% of the company's annual revenue, but it has received significant attention from investors. The applications of this product line mainly include: 1. Tempus Time provides AI-driven CRO services, which can match difficult-to-treat patients with pharmaceutical companies for clinical trials within 14 days, while the industry average is 3 to 6 months. 2. Tempus Next provides clinical decision support for hospitals and doctors. It identifies and measures care gaps for cancer and heart disease patients using relevant applications or algorithms, providing doctors with real-time treatment recommendations for precision treatment. 3. Olivia gathers patient health data and uses AI technology to provide valuable health insights, helping patients better manage their own health. From Tempus' revenue structure, genomics is still the company's largest revenue business, but its revenue growth has slowed down. Therefore, the company has been expanding its business coverage areas in recent years, not limited to oncology but expanding to cardiovascular, central nervous system (CNS), and other areas. Setting genomics aside, Tempus has been successful in commercializing the "data monetization" field. Its data services have become the core business driving the company's performance growth, mainly based on a business-to-business (B2B) model, providing services such as clinical recruitment matching, accelerating clinical registration, and improving registration progress for pharmaceutical companies or life science companies. It is not difficult to see that Tempus has built a core barrier with its data, and the three major businesses have formed a flywheel effect. The applications launched by the company are based on evolved algorithms trained on a large amount of data, and can potentially continue to bring about changes in precision medicine or industry efficiency. In addition to Tempus' surge, pharmaceutical company Recursion and doctor service company Doximity have also experienced significant growth. The growth of AI healthcare stocks in the US can be reflected in the following points: 1. AL genomics/AI tests. BGI Genomics (300676.SZ): the most direct mapping target to Tempus. As a leading domestic genomics sequencing company, it has differentiated competitive advantages in scenarios such as early cancer screening and precision diagnosis, with a global leading gene database (covering over 30 million real clinical treatment data), and continuously expanding rare disease, cancer, and other specialty data sets through cooperation with medical institutions. They have proposed the GBI ALL innovation paradigm and built the multi-modal large model GeneT, enhancing commercial potential in various applications such as precision medical testing, cancer early screening, personalized health management, hospital collaboration, and data monetization (exploring data licensing and AI service fee models). 2. AI doctor services, AI medical insurance. MEDLIVE (02192): a leading online platform for professional physicians in China, which has integrated DeepSeek to accelerate AI commercialization. According to the company's financial report, as of 1H24, MEDLIVE's platform has over 4 million registered physicians, accounting for 88% of licensed physicians in China. The platform has 7 million registered users, 2.5 million monthly active users, 5.98 million paid clicks, with a 40% year-on-year growth. MEDLIVE's main businesses include precision marketing and enterprise solutions, medical knowledge services, and intelligent patient management services. The company continues to invest in R&D and has launched China's first large model-driven AI doctor MedliveGPT (MEDLIVE large model), which has been filed with the National Cyberspace Administration of China. This large model is based on the deep learning Transformer framework, integrating NLP, CV, and other cutting-edge technologies. Enriched with medical data resources during the training process, it effectively addresses the common "illusion" problems in general large models, ensuring the accuracy and reliability of the generated content. 3. Pharmaceuticals + AI. XTALPI-P (02228): with AI drug discovery as the foundation, the company has expanded into the AIforScience field, leveraging AI to shorten the research and development cycle of drugs and materials, and improve development returns. In terms of customer cooperation, the company has cooperated with 16 of the world's top 20 pharmaceutical companies, with 16 collaborations with JensenTech; in 2024, it signed a $135 million material development contract with Xinhu Order, and conducted experimental fields with United Arab Emirates on soil thickening agents. In terms of cooperation pipeline progress, the fastest progress is the global first artificial intelligence organ drug SIGX1094 developed in collaboration between JensenTech and Cristal, which has been granted the FDA fast track designation and is expected to significantly shorten the approval cycle. 4. AI medical data. YIDU TECH (02158): through the full industry chain layout of "medicine-insurance-patient", deep cultivation of big data platforms, life science solutions, and health management, with 261 real world research projects, independently developed AI medical brain YiduCore (in the 2024 MedBench evaluation in Shanghai AI lab, YiduCore ranked first in the three dimensions of "medical knowledge Q&A," "medical language understanding," and "medical safety and ethics"), analyzing and processing over 5.5 billion medical records, covering disease knowledge graph construction, multi-source heterogeneous medical data processing, and intelligent decision support, integrating advanced models such as DeepSeek-V3, YiduCore further enhances data processing efficiency and clinical decision accuracy. 5. Internet healthcare + AI. ALI HEALTH (00241): Its main businesses include medical e-commerce services, medical health, and digital services. According to the company's financial report, as of 24Q3, there were over 230,000 licensed physicians, pharmacists, and nutritionists providing online health consulting services through ALI HEALTH, an increase of over 20,000 year-on-year. In the field of medical large models, ALI HEALTH continues to explore applications in the medical e-commerce field, continuously improving user experience and search conversion efficiency. Based on its leading digital capabilities, ALI HEALTH continues to structure the product data, including the category, model, and factors that influence user decisions, gradually building a complete "product center." This allows users to search and consult customer service through large models, presenting results that accurately and comprehensively express the objective attributes of the products in order of decision priority, helping users improve their experience and search efficiency.Of course, in addition to the above points, the application scenarios of AI in healthcare are showing a vigorous development trend. This includes multiple important areas such as AI imaging, AI-assisted diagnosis, AI health management (chronic disease management), and AI smart healthcare. Among all these rich application scenarios, the biggest beneficiaries are undoubtedly companies with rich data assets. With the powerful technology of AI, these companies can fully exploit the value of data, combine it with advanced algorithms and models, and achieve a synergistic effect between data and technology. This synergistic effect will create a multiplier effect for the development of companies, not only accelerating their business innovation and product upgrades, but also enabling them to occupy a more favorable position in the market competition, driving the rapid development of the entire AI healthcare industry.