Artificial intelligence is no longer an abstract promise in India’s healthcare system; it is now a structural tool being built into public health delivery, especially for a country whose size and population demand solutions that can scale quickly, reliably and affordably. What makes India’s approach notable is not technological ambition alone, but the decision to embed AI within the state’s public health machinery rather than leaving it to private pilots and urban hospitals. The Government of India’s latest statement in Parliament offers a rare, detailed window into how AI is being deployed, and why its real test lies in its ability to strengthen rural healthcare, the part of India that has historically remained underserved, understaffed and under-diagnosed.

The Ministry of Health and Family Welfare’s written reply in the Lok Sabha makes it clear that India is institutionalising AI within its public health architecture. The Ministry has designated AIIMS Delhi, PGIMER Chandigarh and AIIMS Rishikesh as Centres of Excellence for Artificial Intelligence to “promote development and use of AI-based solutions in health”. This signals a shift from ad-hoc experimentation to a coordinated national strategy—something many countries with far smaller populations have struggled to achieve. Through collaborations with bodies such as the Central Tuberculosis Division, ICMR, IISc, CDAC-Mohali and even Wadhwani AI, the government is now developing and deploying AI tools that are already touching millions of patients.

One of the most important examples is MadhuNetrAI, the AI-based diabetic retinopathy identification tool. It has been implemented across 38 facilities in 11 states and has analysed more than 14,000 retinal images, benefiting over 7,100 patients. While these numbers may appear modest in a country of India’s scale, their significance lies in the model they demonstrate rather than the raw volume alone. Crucially, the tool enables “non-specialist health workers to conduct screenings”, automating detection and ensuring standardised triage — a model that directly addresses India’s shortage of specialists in rural districts. Similarly, under the TB elimination programme, the ‘Cough Against TB’ AI solution has screened more than 1.62 lakh individuals between March 2023 and November 2025, delivering an additional yield of 12–16 per cent in TB detection. In public health terms, even marginal percentage gains at this scale translate into thousands of lives detected earlier—and potentially saved. These are precisely the kinds of gains possible only when technology is able to amplify limited human capacity.

Perhaps the most far-reaching intervention is the integration of a Clinical Decision Support System into e-Sanjeevani, India’s national telemedicine platform. Since April 2023, the Ministry said, “282 million e-Sanjeevani consultations have benefited from standardised data capture and AI-based differential diagnosis recommendations”. Few countries in the world can claim AI-assisted clinical decision-making at this population scale, especially within a publicly funded system. In a sprawling country where access to doctors is uneven, this scale matters. It also underlines why India’s AI strategy in health must remain focused on expanding rural access, not merely urban efficiency.

Globally, too, AI is emerging as a force-multiplier in diagnostics and early detection. The World Economic Forum notes that with 4.5 billion people worldwide lacking access to essential healthcare, AI can help bridge the gap. It cites examples of AI spotting fractures missed by doctors, predicting the onset of diseases years in advance, and analysing stroke scans with double the accuracy of human specialists. For India, these global benchmarks are less about comparison and more about validation—that its policy direction is aligned with where evidence, not hype, is pointing. These advances are reminders that India’s direction is aligned with global evidence – that AI can significantly raise diagnostic accuracy and lower the burden on strained health systems.

But as the WEF cautions, the benefits of AI depend on responsible deployment, human oversight and strong regulation. Without these guardrails, AI risks deepening inequalities rather than correcting them. Here, too, India has moved early, with the government reaffirming adherence to the Digital Personal Data Protection Act 2023, the IT Act 2000, ICMR’s Ethical Guidelines on AI in healthcare and MeitY’s AI Governance Guidelines.

India’s opportunity now is to make AI the backbone of an equitable healthcare system – one that brings early detection, specialist-grade screening and standardised diagnosis to the last village. The real measure of success will not be the sophistication of algorithms, but whether a woman in a remote block or a daily-wage worker in a tribal district receives timely, accurate care because of them. If AI can help India bridge its rural health gap, it will not just transform care delivery; it will redefine what universal health coverage looks like for a billion-plus people.

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