With the rapid development of artificial intelligence (AI) technology, internet healthcare platforms are accelerating their adoption of large language models to enhance service efficiency and user experience. Xie Fangmin, leading Ark Health (06086.HK), noted that over 80% of medical consultations involve repetitive questions, wasting patients' time and burdening doctors. This highlights the growing need for AI to alleviate this pressure on healthcare professionals.
The popularity of DeepSeek in early 2023 sparked significant interest in AI applications among major internet healthcare platforms. Ark Health has integrated advanced models like DeepSeek-V3 and DeepSeek-R1, and established a strategic partnership with Tencent Cloud and Tencent Health to explore innovations in pharmaceutical distribution and health management. Meanwhile, WeDoctor's health management application, CareAI, has also fully integrated DeepSeek technology. Ping An Good Doctor (01833.HK), an industry pioneer, became one of the first medical service platforms in China to deploy DeepSeek, demonstrating a strong demand for AI technology.
Image Source Note: Image generated by AI, licensed through Midjourney
Following the pandemic, more patients opted for online medical services, boosting industry recovery. While online penetration in chronic disease management remains relatively low, internet healthcare platforms hope to leverage AI to attract more doctors. Although relaxed policies allow for multi-point practice by doctors, time management remains a challenge. Therefore, efficiently utilizing AI to improve consultation efficiency is crucial.
AI is continuously enhancing the quality of healthcare services. Ark Health's financial report shows that its "Smart Healthcare New Ecosystem" platform significantly improved user engagement and loyalty, with registered users increasing from 42.7 million to 49.2 million and a repurchase rate of 84.7% for paying users. Ping An Good Doctor's report also indicates that its AI-assisted diagnosis boasts over 95% accuracy, showcasing AI's immense potential in healthcare.
However, despite the rapid advancements in AI technology, Xie Fangmin emphasizes the critical importance of trust in medical AI. AI training relies on historical cases and clinical data, and data quality directly impacts AI reliability. To ensure accuracy, Ark Health employs various measures to optimize its knowledge base and models, and conducts rigorous testing.
In the future, as AI adoption accelerates across internet healthcare platforms, the industry will experience increased efficiency while simultaneously facing greater challenges related to trust and reliability.
