Qure.ai today unveiled its latest report, ‘AI in Action: Transforming Health Outcomes Across India’s Care Spectrum’, at the India AI Impact Summit, outlining how artificial intelligence is being deployed at scale across India’s public healthcare system to address critical challenges such as tuberculosis, lung cancer, and acute neurological conditions.
The report consolidates real-world evidence from large public health programmes, state-wide deployments, and multi-country clinical studies, demonstrating how AI, when embedded into existing healthcare workflows, can accelerate diagnosis, reduce system-level delays, and improve access to timely care without adding cost or operational complexity for patients or providers.
Central to the report is the role of state-level partnerships in enabling AI adoption at population scale. Across Maharashtra, Karnataka, Goa, Punjab and other states, governments and public health agencies have integrated AI into routine imaging and emergency care pathways to strengthen detection, triage and follow-up.
● In Maharashtra, AI-enabled incidental screening across public and private facilities contributed to an estimated 35% increase in tuberculosis detection, including among asymptomatic patients undergoing X-rays for unrelated reasons.
● In Karnataka, a government-led partnership enabled the incidental detection of over 6,400 TB cases alongside high-risk lung nodules through a single AI-driven workflow.
● In Goa, a statewide public health deployment screened over one lakh routine chest X-rays, leading to 20 confirmed lung cancer diagnoses through structured referral pathways.
● In Punjab, a state-supported hub-and-spoke stroke network reduced diagnostic turnaround time by up to 85%, protecting the critical “golden hour” even in district hospitals.
Beyond routine care delivery, the report illustrates how AI is being applied to large-scale disease surveillance and national public health initiatives. During the Maha Kumbh Mela, one of the world’s largest mass gatherings, AI-powered chest X-ray analysis was deployed for rapid tuberculosis surveillance in a high-density, high-risk environment. The system flagged abnormalities in 36% of X-rays, enabling early identification and triage of presumptive TB cases and offering a replicable model for mass gatherings and outbreak-prone settings.
Speaking at the launch of the report, Ankit Modi, Founding Member and Chief Strategy & Growth Officer, Qure.ai, said, “What this report shows is not just where AI has been deployed, but where public healthcare is headed. Through state partnerships, AI is moving from being an intervention to becoming part of the system itself, built into how screening, surveillance, and emergency care are delivered. As these models scale, AI has the potential to consistently shift detection earlier, reduce delays across care pathways, and make continuity of care the default rather than the exception, using infrastructure that already exists.”
In addition to on-ground implementation outcomes, the report draws on independent Health Technology Assessment (HTA) evaluations conducted under the Government of India, which validate AI-powered chest X-ray screening as both clinically effective and cost-saving for tuberculosis detection. The assessments show a reduction of approximately ₹10,000 per TB case detected compared to existing diagnostic pathways, reinforcing the case for AI as a scalable intervention that can strengthen public health programmes without increasing system costs.
Taken together, the evidence presented in AI in Action points to a clear shift in how India’s public healthcare system can evolve, by embedding AI as a foundational layer across screening, surveillance, care coordination, and emergency response. As state partnerships deepen and these models scale, AI has the potential to move healthcare delivery from reactive to proactive, enabling earlier intervention, more reliable follow-up, and stronger system-wide resilience across India’s care continuum.
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