New Delhi: Artificial intelligence can become a major healthcare access catalyst in India, but its value will depend on moving beyond isolated pilots to solutions that improve outcomes, reduce costs and integrate effectively into real healthcare systems, experts said at the ETHealthWorld Healthcare Leaders Summit.
During the session, “Is ‘AI’ the Care Catalyst Expanding Reach, Scaling Impact?”, moderated by Prathiba Raju, Senior Assistant Editor, ETHealthWorld, the panel examined what it will take to move AI from experimentation to scaled clinical and public-health deployment.
Dr. Saurav Basu, Senior Scientist, ICMR, said India already has several AI applications in screening and radiology, but their effectiveness must be assessed against existing standards of care.
“Screening might provide you with a diagnosis, but AI doesn’t provide care. Healthcare systems provide care,” he said, stressing that downstream capacity is crucial, particularly in rural and low-resource settings.
Basu also warned against algorithmic bias when AI models are trained on datasets that fail to represent India’s demographic and geographic diversity. Validation, he said, must happen across multiple settings rather than at a single institution. “The best solution should go forward,” he said, calling for independent validation frameworks to identify tools that deliver the greatest public-health value.
J. P. Dwivedi, CIO, Rajiv Gandhi Cancer Institute & Research Center, said clinical adoption is no longer necessarily AI’s biggest barrier. “For a change, this is the first time that clinical adoption is pulling us rather than pushing back,” he said.
He highlighted practical applications ranging from automated classification of patient records to AI-generated clinical summaries and radiology trend analysis. At his institution, AI-assisted document processing has reduced a task that previously took several minutes to about a minute, he said.
Dwivedi, however, cautioned against fragmented adoption. “AI should never be deployed in a siloed manner,” he said, advocating a small number of orchestrated platforms integrated into hospital workflows. Despite advances in clinical support, he maintained that final clinical authority must remain with doctors.
Kalyan Sivasailam, Co-Founder, 5C Network, argued that AI should change healthcare economics by reducing work rather than adding another software layer.
“AI has to be deflationary in nature,” he said. “AI is almost a form of labour.”
He said AI-enabled radiology networks can make specialist expertise available in smaller cities, reducing the need for patients to travel to major metros. Smaller hospitals, he added, are often highly receptive to such technologies because they can leapfrog traditional specialist shortages.
For the panel, AI’s real test will not be the number of pilots launched, but whether technology can make high-quality diagnosis and specialist expertise available to more patients while remaining clinically validated, economically viable and integrated into care delivery.
