Experts discuss how AI can bridge gaps in India’s public healthcare system

At TechSparks 2026, industry experts discussed the challenges of integrating artificial intelligence (AI) into India's public healthcare system. Dr Geetha Manjunath, Founder and CEO of Niramai Health Analytix, Debraj Banerjee, Global technology investor and General Partner at Fundamentum Frontier Advisors, and Shekar Sivasubramanian, Head of Wadhwani AI, highlighted three main challenges: rigorous clinical validation, integration with existing public health infrastructure, and the need for capital investment to scale solutions across India's diverse healthcare ecosystem.

One of the biggest barriers to adoption is prioritizing rapid product development over clinical validation, according to Manjunath. AI tools can be built quickly using readily available datasets, but real-world deployment requires reliable results. She emphasized that a technology's performance must be tested in real clinical settings, including rural areas with limited diagnostic infrastructure, before it can be recommended for widespread use.

Integrating AI into India's public health system is another major challenge, particularly in understanding the systems used by both central and state governments. Wadhwani AI's Shekar Sivasubramanian emphasized that companies must work closely with government officials, training users and adapting solutions to existing workflows. With over 150,000 primary health centres across India, each application requires significant integration and adaptation.

Affordability and accessibility are also crucial for successful AI adoption in public health. Niramai's thermal imaging and AI-based breast cancer screening technology aims to bring the cost of screening below Rs 50, addressing barriers such as discomfort with physical procedures and encouraging women to seek screening. Key requirements for successful AI adoption include affordability, accessibility, acceptability, accuracy, timely results, and clear accountability.

Investors face additional hurdles, including navigating regulatory approvals, financing requirements, and reaching customers in underserved populations. Deep-tech companies need an ecosystem that supports the journey from product development to commercialization, with a focus on hyperlocalization and segmentation. Venture capital is just one part of the ecosystem, which also includes healthcare providers, regulators, investors, and commercial partners.