“Doctors who use AI will replace doctors who do not.”
At the India Today AI Summit 2026, a panel of clinicians and policymakers wrestled with a practical question: what happens when artificial intelligence becomes the first port of call for patients?
Dr Naresh Trehan, Chairman and MD, Medanta – The Medicity; Anjali Kaur, Senior Associate (Non-resident), Chair on India and Emerging Asia Economics, Center for Strategic and International Studies; and Vivek Rajagopal, Group Chief Analytics & AI Officer, Narayana Health, opened the debate and the conversation soon ranged from immediate patient anxiety to system-level governance.
“AI is a very positive thing to happen, but at the same time, it can trigger anxiety reactions which are unfounded till you find the right help,” said Dr Naresh Trehan, stressing that tools such as chatbots should be a component of care, not its entirety.
ACCURACY AND DATA
Dr Geetha Manjunath, Founder, CEO & CTO, NIRAMAI Health Analytix described how her company trained models for breast-cancer triage. “We had to look at all of these five million data points,” she said, explaining that thermal images, mammograms, ultrasound and biopsy records took years to collect.
Her point was blunt: accuracy is only as good as the training set, and developers must design for the populations they intend to serve. She added that clinical validation and regulatory clarity are prerequisites before any diagnostic tool is released.
ACCESS AND AFFORDABILITY
Vivek Rajagopal argued that AI’s most immediate value is operational: cutting inefficiency in hospitals, reducing patient wait times and improving triage.
“If you are trying out fancy AI projects where your end objective and your path to the objective is not clear, the person who pays for this AI gamble is the patient,” he warned.
Panelists repeatedly returned to the affordability gap: private hospitals in India show unexpectedly low occupancy not because demand does not exist but because access, cost and trust limit uptake.
LOCALISATION, ETHICS AND GOVERNANCE
Anjali Kaur urged designers to build for the Global South from the start.
“Low bandwidth environments, vernacular languages and community clinics have to be part of the design,” she said, warning against bolt-on solutions that fail to interoperate with national health architectures.
The group also flagged mental health as uniquely fraught: conversational agents can offer solace, but they do not bear human accountability.
“Do not outsource your mental health to chatbots,” Dr Geetha Manjunath cautioned.
A WAY FORWARD
Speakers sketched a roadmap: mandate representative datasets, require clinical validation, set clear regulatory rules and prioritise low-cost, low-bandwidth deployments for community health workers.
India’s genetic diversity, Dr Naresh Trehan suggested, could be an advantage for global drug discovery if datasets are harnessed responsibly.
The panel concluded with a reminder: AI is principally a governance and trust challenge; technology will follow if institutions and investors define clear purpose, ensure accountability and measure outcomes rather than novelty.
They urged healthcare leaders to align pilots with measurable returns, so costs do not fall on patients. The message was practical: build for people, not for prestige. Always.
