At a Glance

• AI is not new, but foundation models are: The agentic era of reasoning large language models (LLMs) is emerging, with mounting evidence that clinical tasks can be performed at a human level of competence.

• India’s healthcare infrastructure is becoming AI-ready, supported by government initiatives and a thriving start-up ecosystem, as well as rising electronic medical record (EMR) penetration, private capital, and clinician acceptance.

• In AI deployments, value is currently concentrated in a narrow set of use cases (e.g., workflow automation and ambient scribing, among others) directed toward efficiency and patient experience gains while business ROI remains difficult to demonstrate in near-term.

• Several high-potential AI use cases present large whitespace despite clear demand, including remote patient monitoring, operation theatre and intensive care unit (ICU) optimization, post-discharge chronic disease management, and claims management, creating compelling opportunities for AI start-ups.

• Implementation readiness remains uneven - data quality, workflow integration, clinician trust, and change management remain the primary barriers to scale, favoring start-ups with deep healthcare domain expertise alongside AI capabilities.

Why India, Why Now

India is reaching an inflection point in healthcare AI adoption. The foundations for scale are rapidly falling into place, powered by five structural tailwinds: government-led digital infrastructure, rising EMR penetration, significant private capital, a vibrant entrepreneurial ecosystem, and one of the world’s deepest AI talent pools.

How We Have Assessed the ‘AI in Healthcare’ Opportunity

This report takes a patient-first view of AI adoption, mapping friction across all touchpoints in the patient journey, from outreach to post-discharge care, and examining where AI can help address these problems.

Grounded in research and interviews with leading hospitals, diagnostic labs, healthcare start-ups, investors, and other ecosystem participants, the report evaluates use cases through three critical lenses, Value, Deployability, and Trust, to distinguish what is ready to scale now, what providers should build toward, and what remains a future opportunity.

Finally, the report identifies emerging pathways to scale and lays out actionable imperatives for providers and founders to move AI from pilots to practice, and ultimately translate its potential into better healthcare delivery.