UP Allocates INR 2,000 Cr to Boost AI in Healthcare

The investment will support initiatives across medical devices, pharmaceuticals, MedTech, and AI-based entrepreneurship.

Chief Minister Yogi Adityanath has announced that Uttar Pradesh is investing INR 2,000 Cr to transform healthcare delivery through artificial intelligence, aiming to make policies more effective, improve disease tracking, and ensure services reach every citizen efficiently.

Uttar Pradesh has steadily leveraged technology to strengthen public services, particularly in healthcare, over the past decade. CM Yogi highlighted that AI, when applied responsibly, can significantly improve the accuracy of health policies and outcomes.

He said, "Artificial Intelligence is emerging as a powerful instrument to transform governance from a reactive approach to a proactive one."

Under the UP AI Mission, projects worth around INR 2,000 Cr will be implemented over the next three years, positioning the state as a national leader in AI-driven healthcare.

The investment will support initiatives across medical devices, pharmaceuticals, MedTech, and AI-based entrepreneurship. Key developments include a Medical Device Park, a Pharma Park, a MedTech Centre of Excellence in Lucknow, an AI and Innovation-based Entrepreneurship Center in Gautam Buddha Nagar, a Center of Excellence at IIT Kanpur, and the transformation of Lucknow into an AI City.

Moreover, the Chief Minister added, "By enabling real-time data collection and feedback on epidemics and vector-borne diseases, AI can support informed decision-making, stronger policies, and better outcomes".

“AI must remain human-driven, not the other way around," he stressed.

Over the last eight years, technology has also improved welfare delivery, increasing transparency and reducing inefficiencies.

Medical colleges have increased from 40 to 81 since 2017, while ICUs, oxygen plants, dialysis units, blood banks, and digital diagnostics are now available in all districts. AI is also being used to monitor tuberculosis patients, treatment adherence, and high-risk areas.

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