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India’s healthcare sector may be advancing rapidly in artificial intelligence (AI) adoption, but its clinical workforce must be equally prepared for an AI-first future. That's not a technology gap, it's a training gap, says Saurav Kasera, co-founder & CEO, CLIRNET. He further pinpoints areas for improvement in terms of clinical training, fragmented patient data and overburdened clinicians for AI to meaningfully improve patient care.
Kasera further explains that large hospitals are moving fast on AI. Its frontline professionals, doctors and nurses treating the majority of India, are still working without it. That's not a technology gap, it's a training gap. We haven't taught clinicians how to use AI as a second opinion, not a replacement for judgment. Fix that in medical education now, and India leapfrogs rather than plays catch-up.
He further adds that it is a problem related to system. Patients repeat their history at every visit because records don't travel with them. Doctors seeing 70+ patients a day default to shortcuts because there's no time for anything else. And referrals get delayed because the incentives don't favour sending a patient elsewhere. These are fixable design flaws, not a talent shortage.
Kasera notes that evidence-based medicine must become the new standard of care across India's healthcare system. “We've been practicing medicine on evidence built for other populations. The next standard of care has to come from Indian outcomes data, at scale, and it has to be realistic about what's available on the ground. A guideline only works if the infrastructure to follow it actually exists,” he states.
The next phase of India's healthcare transformation is beyond infrastructure expansion. Kasera further says, “Three things will separate the leaders from the rest: turning patient data into decisions, not just digital records; paying for outcomes instead of volume; and using AI to multiply what clinicians can do, because we will never train doctors fast enough to close the gap alone. We've built the hospitals. The next decade is about what happens inside them.”
“India can build a more future-ready and clinically resilient healthcare workforce based on three priorities. Build tools that save clinicians time, as anything that adds work won't get adopted. Train doctors to work confidently with probability, not just certainty, because that's how AI actually communicates. And settle the accountability question: who's responsible when a doctor follows or overrides an AI recommendation? That uncertainty is holding back adoption more than any technology limitation,” Kasera concludes.
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