NEW DELHI: India’s healthcare system is coming under growing pressure from an ageing population, rising burden of chronic diseases and shortages of doctors, nurses and hospital beds, according to a knowledge paper released by Union Health Minister J P Nadda on Saturday. The report says artificial intelligence (AI) can help bridge this widening gap by extending specialist expertise, improving diagnosis and expanding access to quality healthcare, particularly in smaller hospitals and underserved areas.Nadda released the knowledge paper, “AI in MedTech: Revolutionizing Healthcare Through Artificial Intelligence,” at the 9th edition of India Medical Device 2026, organised by the Department of Pharmaceuticals in association with FICCI.The report estimates India’s population at 1.47 billion in 2026 and says more than 65% of deaths are now due to non-communicable diseases such as heart disease, diabetes and cancer. It projects the population aged 60 years and above to cross 230 million by 2036, further increasing demand for long-term healthcare.Despite expansion in healthcare infrastructure and medical education, shortages persist. India has 9.6 doctors per 10,000 population, compared with the global average of 18.3. It has 27.2 nursing personnel per 10,000 against 40.5 globally, 15.9 hospital beds per 10,000 compared with 33, and only 4 MRI scanners per million people, against the global average of 19, the report says.According to the report, AI is not intended to replace doctors but to multiply specialist capacity by assisting in diagnosis, clinical decision-making and screening. AI-enabled diagnostics are expected to be the first large-scale application, helping extend specialist expertise to primary and secondary healthcare, improve productivity and reduce inequalities in access to care.
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The report says India has already built the foundations for AI in healthcare through initiatives such as the Ayushman Bharat Digital Mission, IndiaAI Mission, SAHI, BODH and the National Medical Devices Policy, 2023. It says the next challenge is to move AI from successful pilot projects to routine clinical use by creating AI-ready health data, a predictable regulatory framework and reimbursement mechanisms for AI-enabled technologies.
