Indian healthcare providers are moving artificial intelligence from pilots into operational use cases that ease administrative burdens on clinicians
NEW DELHI — Indian healthcare providers are moving artificial intelligence from pilots into operational use cases that ease administrative burdens on clinicians, a report said on Tuesday.
Government initiatives, rising Electronic Medical Record (EMR) penetration, deployment of private capital, a thriving start-up ecosystem and clinician acceptance are strengthening the enabling environment, the report from Bain & Company and HealthQuad said.
However, most providers remain in controlled testing with meaningful scale limited to operational workflows.
Electronic Medical Record (EMR) adoption in India at nearly 35 per cent remains well below the US and UK and is concentrated among larger urban hospital chains, while most small- and mid-sized hospitals continue to rely heavily on paper records.
India’s framework for adaptive and autonomous clinical AI is still evolving, particularly around accountability, data governance and clinical validation.
The country has deep AI capabilities, but much of that talent is currently directed toward global markets, the report said.
Indian start-ups are already building across the patient journey including pre-visit and access, diagnostics and inpatient treatment, and post discharge care.
“AI adoption in Indian healthcare is still early, but the conditions for it to scale are strengthening quickly,” said Dhruv Sukhrani, Head of Bain & Company’s Healthcare & Life Sciences practice in India.
"The technology itself has advanced significantly; the harder question now is how providers redesign workflows, manage change and build trust among doctors and nurses," Sukhrani said.
Frontier models now match or outperform pre-licensed medical professionals in some controlled clinical reasoning tests. Meanwhile, these capabilities are becoming more accessible as the cost of frontier AI models has fallen by approximately 92 per cent since 2023.
The report identified significant headroom areas such as remote patient monitoring, operating theatre, ICU optimization, and post-discharge chronic disease management.