Indian healthcare AI has moved past the model-building phase. The harder problem now — getting the technology into the fabric of everyday care — is only just beginning.

Added to Saved Stories in Login VIEW SAVED STORIES .inc42-toggle-item-popup { display: none; position: relative; } .toggle-item-close { text-align: end; padding: 8px 12px 0px 10px; position: absolute; right: 0; cursor: pointer; } .toggle-items-content-main { display: block; position: relative; top: 27px; left: -204px; border-radius: 12px; background: #FFF; box-shadow: 0px 4px 24px 0px rgba(100, 100, 100, 0.25); width: 435px; height: 115px; } .toggle-items-content { display: flex; align-items: baseline; justify-content: center; padding-top: 22px; } .toggle-items-content .items-content-text .h4-saved-story{ color: #000; font-size: 20px; font-style: normal; font-weight: 700; line-height: normal; text-transform: capitalize; margin: 2px 0 10px 6px; } .toggle-items-content .items-content-text .myInc42-plus-dark { width: 100px !important; } .toggle-items-content .items-content-text .myInc42-light { width: 80px !important; } .toggle-items-content .items-content-text img{ height: 22px; } .view-my-feed-btn { width: 100%; text-align: center; display: flex; justify-content: center; } .view-my-feed-btn a { width: auto !important; } .view-my-feed-btn button { border-radius: 4px; background: linear-gradient(180deg, #DA1B4D 0%, #E23026 100%); color: #fff; font-size: 12px; display: inline-block !important; min-width: 162px; width: 162px !important; height: 34px !important; font-style: normal; font-weight: 700; line-height: normal; padding: 10px; cursor: pointer; } .CustomIconStyled { position: absolute; right: 180px; top: -80px; } .SubDropdownModelShare .sub-arrow-icon { width: 76px; height: 80px; position: relative; overflow: hidden; box-shadow: none; } @media (max-width:767px) { .toggle-items-content .items-content-text .h4-saved-story{ margin: 4px 0 10px 6px; font-size: 18px; } .toggle-items-content { align-items: center; } }

Healthcare AI is almost always framed as a promise — sharper diagnostics, faster decisions, better outcomes.

In India, that promise is now beginning to take shape across radiology labs, pathology workflows, and public health programmes. 

In a country that severely lags in access to healthcare, the doctor-population ratio in India for the allopathic treatment category is estimated to be 1:1200 (as of late 2025), which is below the WHO recommended level of 1:1000. And while that disparity does not seem grave, this is based on 80% availability of approximately 13.88 Lakh registered allopathic doctors for a population of over 1.4 Bn. 

While we are seeing plenty of healthcare AI startups, the tension between the promise and on-ground reality is something that is yet to be resolved. Can AI truly solve this gap? Because if so, no other country needs this to happen as much as India. 

From Models To Medical Infrastructure

The first wave of healthcare AI was about building models — improving accuracy, training on more data, and proving technical feasibility. That phase has matured.

Ankit Modi, cofounder, and chief strategy and growth officer at Qure.ai, which makes AI for medical imaging, says the real gap today lies in deployment. 

Ankit Modi, cofounder, and chief strategy and growth officer at Qure.ai, which makes AI for medical imaging, says the real gap today lies in deployment. 

In many hospitals, AI still operates as an add-on. It analyses data but doesn’t actively participate in clinical workflows. The shift now is toward making AI a native layer within healthcare systems — embedded across screening, diagnosis, and follow-ups.

Jadeja Dushyantsinh Anopsinh, AI advisor for eye screening startup Remidio, adds that much of healthcare AI is still focused on the wrong layer. “The real whitespace is at the risk triaging layer, before patients ever reach a specialist,” he says.

In one of Remidio’s programmes in Kerala, for instance, nearly 99% of diabetic retinopathy cases detected were previously unknown to patients, highlighting how hospital-centric AI misses large parts of the population that never enter formal care systems.

“There’s also a deeper imbalance… much of AI innovation is concentrated in high-resource environments, however, the biggest challenges… start at the first point of care,” Modi added.

The focus is shifting from........

© Inc42