India healthcare AI adoption is accelerating, but hospital leaders say integration, workflow fit and scaling successful pilots remain the biggest obstacles.
NEW DELHI: India healthcare AI is generating a growing number of pilots across screening, diagnostics and hospital operations, but experts say the bigger challenge is getting those tools embedded into everyday clinical care.
Speaking at the sixth ET Healthcare Leaders Summit, hospital and health technology leaders said integration rather than clinician resistance is increasingly becoming the main obstacle to wider adoption.
Why successful AI pilots struggle to scale
Dr Saurav Basu, Senior Scientist at the Indian Council of Medical Research, said India already has numerous artificial intelligence pilots operating across diagnostics, screening and surveillance.
However, he warned that identifying a possible illness is only one part of healthcare delivery. Hospitals must also have the staff, infrastructure and treatment pathways needed to manage patients after an AI system identifies a potential problem.
Basu estimated that about 95 per cent of pilots fail to become fully integrated into the health system, describing the gap between experimentation and routine deployment as a major challenge.
Hospitals want AI that fits existing workflows
J.P. Dwivedi, Chief Information Officer at Rajiv Gandhi Cancer Institute and Research Centre, said clinical acceptance is no longer necessarily the biggest hurdle.
He pointed to applications including automated classification of patient records, clinical summaries and radiology trend analysis. At his institution, AI-assisted document processing has reportedly reduced a task that previously took several minutes to around one minute.
Dwivedi cautioned that adopting multiple disconnected AI tools could create further complexity. Hospitals instead need coordinated platforms that work across existing systems and clinical workflows.
AI must reduce costs rather than add them
Kalyan Sivasailam, co-founder of 5C Network, argued that hospitals are more likely to adopt artificial intelligence at scale when it lowers operational costs rather than creating another technology expense.
That could mean reducing repetitive work, helping specialists process cases faster or decreasing the number of decisions and clicks required during routine tasks.
For India healthcare AI to move beyond demonstrations, hospitals will therefore need evidence that technology improves both clinical outcomes and efficiency.
Data diversity remains another challenge
Experts also warned that AI systems trained on limited datasets may not perform equally well across India’s diverse population.
Differences in language, ethnicity, socioeconomic conditions and healthcare access mean algorithms need representative data and careful real-world validation before being deployed widely.
The Indian government has also recognised these concerns through its Strategy for Artificial Intelligence in Healthcare for India, which emphasises responsible, transparent and people-centred adoption.
What hospitals need next
The India healthcare AI discussion suggests the next stage will depend less on launching new pilots and more on proving that existing tools can work safely inside real hospitals.
Integration, affordability, representative data and measurable patient benefits are likely to determine which technologies eventually move into routine care.
Impact to expect
Better integration could help hospitals automate administrative work, support faster diagnosis and extend specialist expertise to more patients. However, adoption is likely to remain gradual unless AI systems demonstrate clear clinical value without disrupting existing workflows or increasing costs.
