AI application in Indian healthcare rising but adoption uneven: Report

Indian healthcare providers are gradually moving artificial intelligence (AI) from pilot projects to real-world use, but adoption remains uneven across hospitals and clinical workflows, according to a joint report by Bain & Company and HealthQuad.

The report, titled “AI in Indian Healthcare Delivery,” was launched on September 8. It stated that government initiatives, rising electronic medical record (EMR) adoption, private investment, a growing start-up ecosystem, and increasing acceptance among clinicians are creating stronger conditions for AI adoption in healthcare.

However, most hospitals are still testing AI in controlled settings rather than deploying it at scale. Adoption is currently moving faster in operational and administrative tasks, where implementation is easier, and results can be measured more quickly. Clinical applications are emerging mainly among more digitally mature healthcare providers and are largely being used to support, rather than replace, clinical decision-making.

The report is based on interviews with chief information officers and chief technology officers of leading hospitals and diagnostic laboratories, start-up founders and other industry participants, along with secondary market research.

The report said advances in AI are happening faster than most healthcare organisations can adapt. Newer generative and agentic AI systems can increasingly handle multiple steps of a workflow with limited supervision. The amount of expert-level work that AI can complete autonomously has also been doubling every six to nine months since 2023. At the same time, these capabilities are becoming more accessible as the cost of frontier AI models has fallen by approximately 92 per cent since 2023.

For hospitals, this could help reduce the administrative workload of doctors, nurses and other healthcare professionals, allowing them to spend more time on patient care.

But significant gaps remain. For instance, EMR adoption in India is estimated at around 35 per cent, well below levels in the US and UK. EMRs are also concentrated among larger urban hospital chains, while many small and mid-sized hospitals continue to depend heavily on paper records.

Regulatory clarity is another challenge. India’s framework for adaptive and autonomous clinical AI is still evolving, particularly on issues such as accountability, data governance and clinical validation.

The report also pointed to a gap in locally focused AI talent, with much of India’s technology talent serving global markets. At the same time, Indian start-ups are developing AI solutions across the patient journey, including pre-visit care, diagnostics, inpatient treatment and post-discharge care.

The report also identified remote patient monitoring, operating theatre and intensive care unit optimisation, and post-discharge chronic disease management as areas with significant potential for further AI adoption.

For hospitals, the report said AI should be treated as a business transformation rather than simply an IT project.