By N.Dayasindhu & Rishikesha T Krishnan
AI’s ultimate success in India will not be measured by the size of its GPU clusters, but by how our AI applications can help improve the quality of life of our citizens – e.g. when AI can help ASHA professionals detect the number of high-risk pregnancies, or small farmers save significantly on pesticide consumption, or significantly improve the reading and math scores of a child in a remote government school.
The Economic Survey 2026 is pragmatic about how India can leverage AI. A primary objective of the AI Economic Council for India proposed in the Economic Survey, is Human Primacy and Economic Purpose. There is clarity that a national AI adoption policy must be explicitly subordinate to human welfare and economic inclusion.. AI needs to be sensitive to domestic economic realities, and the benefits of AI adoption should accrue to all sectors of the economy and all citizens.
Fortunately for us, Indian innovators are deploying AI applications to solve social and economic problems that are immediate and contextual to India. Applications in health, agriculture, education, urban management, and disaster preparedness show promise. With the right support, many of these can scale to a pan-India market and, at some future point, can be bundled into an India AI Applications Stack, and even be taken to global markets. Let us look at some interesting initiatives.
Healthcare: Niramai has developed a non-invasive, privacy-conscious breast cancer screening tool that uses AI-driven thermal imaging instead of traditional mammography. This tool enables early detection of abnormalities in women of all ages, including those with dense breast tissue where mammography often fails. It is portable and low-cost, making mass screening viable in rural and semi-urban areas. Qure.ai is an AI tool that analyzes X-rays and CT scans in seconds, detecting more than 35 conditions like TB, lung cancer, and heart failure. This solution is very effective in resource-constrained settings where radiologists are unavailable, facilitating rapid triage and treatment in remote districts. AISteth, an AI-powered stethoscope, converts heart and lung sounds into visual waveforms for accurate, remote diagnosis. This low-cost device has a 93% accuracy and empowers frontline health workers in rural India to detect cardiac and respiratory issues early. It bridges critical gaps in specialist care and has the potential to strengthen India’s public health system.
Agriculture: Neoperk is a portable device using near-infrared spectroscopy and machine learning to analyze soil health instantly without conventional lab chemicals. This provides lab-accurate results for 12 key soil parameters in under five minutes. This empowers farmers to make data-backed decisions on fertilizer use, improving soil health and reducing input expenses. CottonAce from Wadhwani Institute for Artificial Intelligence is an AI-based mobile app that allows farmers to upload photos of pests caught in traps to receive instant, localized advice on pesticide application. This app helps thousands of smallholder cotton farmers to protect their crops from pests like pink bollworm, leading to higher quality harvests and increased profit margins. Niqo Robotics uses AI-powered robots equipped with computer vision (day-and-night cameras) to identify pests and weeds in real-time. This enables selective spraying, which ensures chemicals are applied only where needed. This has led to a significant reduction in pesticide use (up to 60-90% in some cases), lowering costs for farmers and reducing environmental toxicity. Cropin is an AI-enabled digital ecosystem that spans farm monitoring, credit risk analytics, and last-mile farmer engagement. It drives sustainable productivity and climate-smart decisions, turning fragmented practices into predictive farming systems ready for global scale.
Education: PadhaiWithAI uses an AI-powered personalized learning platform designed to tackle poor mathematics learning outcomes in government schools. Within just six weeks, the initiative significantly improved pass rates and the performance of high-achievers. It serves as a scalable model for bridging learning gaps in rural Indian education. Rocket Learning has an AI-powered learning companion, Appu (a generative AI elephant), that interacts with parents and children via WhatsApp. It delivers bite-sized, play-based activities to help children under six achieve foundational literacy and numeracy. Belagavi Smart City is integrating deep learning-enabled eBooks into its public library ecosystem. Designed to analyze user behavior and adapt storylines, vocabulary, and difficulty levels in real time, these books have improved engagement and comprehension. There is a 12% improvement in reading speed in just two weeks.
The government can become a powerful ecosystem orchestrator for these grassroots focused AI innovations and help them scale to pan-India high-impact applications. A key focus area of the government could be to assist in market making for these AI applications. For example, the government can facilitate procurement where empaneled domestic AI applications can provide solutions for government (including state government) departments, hospitals, schools, etc. Further, by setting benchmarks for AI in health, agriculture, education, etc., the government can create a trusted environment for customers and citizens to adopt them.
Once these AI applications have proven themselves, the government could facilitate integrating the most impactful applications into an India AI Applications Stack – i.e., solutions built for India’s scale and diversity that are ready for global deployment. We can leverage platforms like the Global Partnership on AI. A strong national governance framework for the Indian AI Application Stack that dovetails with international frameworks like the European GDPR can make the stack a plug-and-play in many countries.
(Rishikesha T Krishnan is Professor of Strategy at IIM Bangalore. N Dayasindhu is Co-founder and CEO of itihaasa Research and Digital.)
