Korea and India outline divergent national strategies for healthcare AI

Korea’s AI Basic Healthcare Strategy is one of the more concrete national blueprints for applied AI we have seen so far. It treats AI infrastructure like public utilities, with a central GPU platform, a national health data hub and a staged rollout of AI tools to primary care, emergency services and drug discovery. That is a template for how a mid sized, high income country can try to capture value from frontier models rather than remaining just a downstream customer of US or Chinese labs.

India’s position, by contrast, is a reminder that talent and digital public infrastructure are not enough without regulatory and payment plumbing. The Praxis–FICCI paper frames AI ready data, lifecycle regulation and reimbursement as the missing middle that keeps promising pilots from becoming nationwide systems. In the race to AGI, these health deployments matter less for raw capability and more for legitimacy. If patients, clinicians and regulators see AI consistently improving care in high stakes settings, it strengthens the political mandate to keep scaling models. Conversely, if only a handful of rich countries can integrate AI into healthcare safely, pressure will grow for more muscular global rules on access, safety and equity.