The world will simply never have enough doctors. The WHO projects a shortfall of 10 million health-care workers by 2030, including more than 3 million doctors. Populations are aging and chronic disease is rising, exacerbated by climate change, and traditional medical training can’t keep pace. In China, the physician workforce has expanded to about 3.1 doctors per 1,000 people, yet sharp rural–urban gaps mean the real shortage is one of distribution, not absolute numbers.

That reality framed the AI for Health panel I moderated at the AI for Good Forum during the World AI Conference in Shanghai in July. Alongside leaders from the Novartis Foundation, Yidu Tech, and the Fosun Foundation, we explored how artificial intelligence can help health systems in two critical ways: boost public health at scale and expand the capacity of the doctors already in service, especially in hard-to-reach areas. This isn’t abstract. AI interprets: our test results, which treatments we get and how much they cost, and it can help address the social determinants of health, which are critical for driving greater global health equity.

Scaling public health impact

Novartis Foundation’s AI for Healthy Cities shows what a population-level approach can do. By integrating municipal, healthcare, insurance, census and academic data, the program predicts cardiovascular risk factors and guides early action. In New York City, it surfaced key drivers such as education gaps, housing instability, poor internet access, limited healthy food, and social isolation.

This allows city officials to redirect resources across multiple city agencies based on clear data. Pilot cities have reported faster interventions and improved prevention metrics within a single budget cycle, illustrating how AI can help governments get ahead of disease risks rather than chase them.

Expanding the reach of every doctor

Yidu Tech, a leading Chinese health-tech firm, tackles the clinical side of the shortage. Its AI decision-support system helps senior physicians in top hospitals manage nearly 100 patient visits per day while simultaneously mentoring junior doctors in smaller facilities. Early pilots show double-digit reductions in misdiagnosis rates and significant time savings. The result: more patients treated locally, less pressure on overcrowded urban hospitals, and better use of scarce specialist expertise.

Strengthening rural medicine

Fosun Foundation’s Rural Doctors Program complements these models by focusing directly on front-line providers. Active in China across 78 counties, it supports about 25,000 village doctors, improving care for over 3 million rural families. The program combines training, insurance, and clinic upgrades and, in pilot areas, is introducing AI-assisted diagnostic tools and big-data analysis to help rural doctors make faster, more accurate decisions. By embedding technology in a long-running, trust-based support network, Fosun shows how AI can extend the reach and resilience of the single doctor who may serve an entire village.

Trust and human connection remain central

Technology can amplify what people already do, but it cannot replace what people must do. Yidu Tech’s Ying Ying stressed that trust is the true currency of adoption: if leading doctors don’t embrace these tools, patients won’t either. In one case, a false record generated by AI was caught only because clinicians and the patient were involved.

Novartis likewise finds that relationships drive results. Local ownership, simple shared goals, and human-centered design remain decisive in aligning agencies and sustaining action. To tackle complex social determinants, all city agencies need to see health as part of their mandate.

Guardrails and equity

Finally, all three panelists warned of bias in data, from under-representation of immigrant or other minority groups to blind spots in rural health records. Without deliberate correction, AI could hard-code yesterday’s inequities into tomorrow’s systems. Combining quantitative data with community insight is essential.

Conclusion

The global doctor shortage isn’t a temporary crisis—it’s a structural limit. AI will not replace physicians, but it can multiply their impact, empower communities to prevent disease, and help entire cities and villages act before illness strikes.

From Novartis’s city-scale analytics to Yidu’s clinical decision support, to Fosun’s trusted rural doctor network, we see a common perspective: pair cutting-edge AI with human trust, local ownership, and constant vigilance against bias. Only then can AI turn the limits of human resources for health into a new era of equitable, preventive health care.

I look forward to further exploring how AI will shape health around the world. Please share your favorite examples, whether they relate to human resources, public health, new treatments, advanced diagnostics or broader personal control of the health care journey. There is a lot for all of us to continue learning as we go further into this new frontier.