According to a research report from CITIC SEC, medical AI is set to accelerate the restructuring of the trillion-yuan pharmaceutical market. The underlying logic for AI in healthcare has undergone a fundamental shift in 2026, with the core change being that payers for AI healthcare are now more clearly defined and possess stronger payment capabilities this year. Consequently, 2026 is anticipated to be a year of greater certainty for the commercialization of AI healthcare, unlocking its commercial potential. It is recommended to focus on five main investment themes and related targets: AI-powered drug discovery, primary care AI healthcare applications, medical data circulation and trading, AI pathology diagnostics, and AI healthcare models with consumer-facing expansion channels. The key views of CITIC SEC are as follows.
Medical AI will accelerate the reshaping of the trillion-yuan pharmaceutical market, and 2026 is expected to be a year of heightened certainty for AI healthcare commercialization. The fundamental logic driving AI in healthcare has changed significantly in 2026, primarily because the payers for AI healthcare are now more clearly identified and possess greater financial strength. Therefore, the certainty of commercialization for AI healthcare is expected to increase this year, opening up the commercial landscape for AI in medicine.
AI-powered drug discovery has achieved substantial technological breakthroughs and is expected to generate significant positive impacts in clinical settings in the future. Considerable progress has been made compared to previous years, with clinical trial data already indicating that AI-developed drugs have a far higher success rate in Phase I clinical trials than the industry average, and their success rate in Phase II trials also ranks high within the industry. With breakthroughs in algorithms targeting protein structures, molecular dynamics (MD), and biology, combined with AI's optimization and restructuring of clinical trial design, AI is poised to create markedly positive effects in clinical practice going forward.
Primary care AI healthcare applications are seeing increased payment certainty for primary care informatization and AI healthcare, supported by special fiscal funds under the "Strengthening the Foundation Project." Starting in 2025, the National Health Commission has prioritized the "Healthcare Strengthening the Foundation Project." According to the People's Daily, in 2025, the state allocated approximately 8.8 billion yuan in various central funds specifically for comprehensively promoting the construction of compact county-level medical communities under this project. In 2026, the National Health Work Conference established the principle of "Strengthening the Base, Stabilizing Secondary Care, and Controlling Tertiary Care," suggesting that state investment in primary care may continue to increase this year, with primary care informatization, AI applications, and health management areas expected to benefit sustainably.
The medical data circulation and trading market holds broad prospects, with medical data holders poised for a revaluation of their assets. A significant payer for medical data is innovative pharmaceutical and medical device companies, and with the upsurge in R&D for innovative drugs and devices, demand for medical data assets is robust. It is anticipated that as national policies on cross-border data flow advance, large multinational pharmaceutical companies are also expected to become payers. Furthermore, the implementation of a trusted data space architecture is likely to establish the foundation for the circulation of medical data assets. Policy and event catalysts in the data trading sector are anticipated in 2026, and the data value of entities such as the healthcare insurance system, public hospitals, ICLs (Independent Clinical Laboratories), imaging and pathology services, internet healthcare platforms, medical examination institutions, and pharmaceutical distributors is expected to be reassessed. Relevant companies are projected to achieve tens of millions of yuan in data-related revenue by 2025, with further growth expected in 2026, and the overall scale of data transactions in the healthcare industry is set to expand rapidly.
AI pathology diagnostics are seeing commercialization potential realized as medical insurance becomes a payer. The National Healthcare Security Administration issued the "Guidelines for Establishing Price Items for Pathology Medical Services (Trial)," which explicitly lists "AI-assisted diagnosis" as an extension item for pathology diagnostics and incorporates it into the pricing structure of pathology service items. This clarifies the charging pathway for applying AI-assisted diagnostic technologies and promotes the use of AI pathology in routine diagnosis and treatment. The commercial potential for AI pathology diagnostics is expected to open up in the future.
AI healthcare models and consumer-facing expansion channels continue to see enhanced model capabilities, promising vast commercial opportunities in both B2B and B2C sectors. Major tech firms continue their strategic deployments, with AI healthcare models like ChatGPT Health and Ant Group's A-Fu demonstrating improved capabilities. 2026 is forecast to be a year of consumer market entry and commercial expansion for AI healthcare, potentially driving a revaluation of B2C channel value. Concurrently, policy support for AI healthcare model applications persists; according to media reports from sources like China National Radio and the "HC3i Zhongshu Xinyi" WeChat public account, AI pilot bases in the medical field are entering the implementation phase in multiple provinces including Beijing, Shanghai, Zhejiang, and Guangdong, which is expected to advance the development and tangible performance of AI healthcare applications, highlighting the broad commercial prospects for AI healthcare models in both B2B and B2C markets.
Risk warnings include potential underperformance of policies promoting AI healthcare, risks of medical malpractice, slower-than-expected development of underlying AI technologies in healthcare, and risks associated with slower-than-anticipated progress in the commercialization of medical AI.
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