Archive · 8 Sep 2026
Indian Healthcare Providers Move AI Pilots Into Practice
Indian hospitals and healthcare companies are starting to use artificial intelligence for more than experiments.
AI is being used mainly to help with hospital tasks and reduce paperwork for doctors and nurses.
Government programs, investments, startups and greater acceptance by clinicians are helping this happen.
But most hospitals are still testing AI carefully.
Electronic medical records are used in about 35% of India, mostly by large hospitals in cities.
Many small and medium-sized hospitals still use paper records.
Rules about responsibility, data and checking AI systems are still developing.
The report says AI could also help monitor patients remotely and support intensive care.
It says hospitals must redesign their work and build trust before AI can spread widely.
Indian healthcare providers are shifting AI projects from pilots toward operational uses that reduce clinicians’ administrative workloads.
Government initiatives, rising electronic medical record adoption, private investment, startups and clinician acceptance are supporting wider AI use.
Most providers remain in controlled testing, with meaningful scale largely limited to operational workflows.
Electronic medical record adoption is nearly 35% and concentrated among large urban hospital chains, while many smaller hospitals still rely on paper records.
The report highlights opportunities in remote monitoring, operating theatres, intensive care and post-discharge chronic disease management.
- Who
- Indian healthcare providers, startups, clinicians and investors, as discussed in a Bain & Company and HealthQuad report.
- What
- Healthcare providers are moving artificial intelligence from pilot projects into selected operational workflows.
- When
- The report was cited on Tuesday; it also says frontier AI model costs have fallen approximately 92% since 2023.
- Where
- India, with adoption concentrated among larger urban hospital chains.
- Why
- To ease administrative burdens and improve healthcare workflows, while addressing challenges involving data, accountability, clinical validation and trust.
- Report authors
- Bain & Company and HealthQuad
- Electronic medical record adoption
- Nearly 35% in India
- Current scale
- Meaningful AI deployment remains largely limited to operational workflows
- Key adoption drivers
- Government initiatives, private capital, startups, rising EMR penetration and clinician acceptance
- Regulatory challenges
- Accountability, data governance and clinical validation for adaptive and autonomous clinical AI
- Model cost change
- Frontier AI model costs have fallen by approximately 92% since 2023
- Potential growth areas
- Remote patient monitoring, operating theatres, intensive care and post-discharge chronic disease management