AI in Healthcare: Remote Monitoring Emerges as the Next Growth Frontier
Indian healthcare providers are moving artificial intelligence beyond pilot projects, with connected care, ICU optimisation and chronic disease management emerging as major opportunities
AI Adoption Shifts from Experiments to Implementation
Artificial intelligence is moving into a new phase in India’s healthcare sector, with hospitals and healthcare providers increasingly focusing on practical applications rather than limited pilot projects. A joint report by Bain & Company and HealthQuad identified remote patient monitoring, operating theatre and intensive care unit optimisation, post-discharge care and claims management as major growth opportunities.
The report, titled AI in Indian Healthcare Delivery, said healthcare providers are already deploying AI to reduce administrative workloads, improve workflow efficiency and support clinicians. However, the next phase of adoption is expected to focus more closely on connected clinical care, where technology can directly improve patient management and healthcare delivery.
Remote Patient Monitoring Gains Importance
Remote patient monitoring could become one of the most important applications of AI in Indian healthcare. By combining wearable devices, connected medical equipment and digital health records, AI systems can track vital signs and identify potential health risks before they become critical.
Such systems could help doctors monitor patients with diabetes, cardiovascular diseases and other chronic conditions after discharge. They may also reduce hospital readmissions, improve follow-up care and allow healthcare providers to manage more patients without requiring frequent physical visits.
For patients in smaller cities and rural areas, remote monitoring could improve access to specialists and reduce the cost and inconvenience of repeated hospital visits. However, the effectiveness of these systems will depend on reliable connectivity, accurate data and timely clinical intervention.
EMR Adoption Remains a Key Constraint
The report highlighted that connected clinical care is still limited by electronic medical record adoption, which currently stands at around 35 per cent. Without structured and interoperable patient data, AI systems may struggle to deliver consistent recommendations or integrate information across hospitals, laboratories and specialists.
Healthcare providers will therefore need to invest in digital infrastructure, data security and workflow integration. Hospitals with stronger data foundations are likely to scale AI faster than those still operating with fragmented or paper-based records.
Falling Technology Costs Support Wider Adoption
The report noted that the amount of expert-level work AI can complete autonomously has been doubling every six to nine months since 2023. At the same time, the cost of frontier AI models has declined by approximately 92 per cent.
Lower technology costs could make AI solutions more accessible to mid-sized hospitals and healthcare startups. Providers without strong in-house technology capabilities may increasingly turn to integrated platforms that combine software, analytics, clinical tools and implementation support.
Trust and Governance Remain Essential
Despite rapid technological progress, AI adoption in healthcare faces important challenges. Data quality, privacy, cybersecurity, regulatory compliance, clinician acceptance and workflow disruption could limit the speed of deployment.
AI systems are more likely to gain acceptance when they support doctors rather than attempt to replace them. Human oversight, transparent decision-making and clinical validation will remain essential, particularly in critical-care environments.
Market Outlook
AI is expected to become an important capacity multiplier for Indian healthcare providers as digital records, government initiatives and private investment expand. Remote monitoring and chronic disease management could offer the strongest near-term growth opportunities because they address rising patient demand while improving healthcare efficiency.
However, long-term success will depend less on access to advanced AI models and more on whether hospitals can integrate these tools into daily clinical workflows. Providers that combine technology with reliable data, trained personnel and strong governance may gain a significant competitive advantage as healthcare moves towards more connected and proactive care.