At the India AI Impact Summit 2026, Qure.ai demonstrated how health systems can embed artificial intelligence (AI) directly into public health infrastructure to enable population-scale screening and disease surveillance.
The discussion unfolded during the panel titled “Public Health Powered by AI: RailTel’s Collaborative Model for AI-enabled Inclusive Healthcare for Bharat and Beyond.” Notably, the session focused on integrating AI within national health programmes as part of routine service delivery rather than treating it as an external add-on.
A Multi-Stakeholder Dialogue on Scalable AI
The panel brought together senior leaders from government, academia, global health institutions, and industry to examine how countries can deploy AI at scale within national health systems.
Participants included Sunil Kumar Barnwal, CEO of the National Health Authority; Prof. Anubha Gupta from Indraprastha Institute of Information Technology Delhi; Jean Philbert Nsengimana, Chief Digital Advisor at Africa Centres for Disease Control and Prevention; and Ankit Modi, Chief Strategy & Growth Officer at Qure.ai.
Shri K. Manohar Raja, Principal Executive Director at RailTel Corporation of India Limited, moderated the session and steered the conversation toward practical models of implementation.
Digital Infrastructure as the Backbone of Scale
Shri K. Manohar Raja emphasized that strong public-sector digital infrastructure enables proven health technologies to scale effectively. He explained that reliable networks and interoperable systems reduce implementation barriers and help technology partners expand deployments across public health programmes in India and internationally.
In other words, infrastructure determines whether innovation remains a pilot project or evolves into a nationwide solution.
National Digital Foundations Enable AI Adoption
Building on this point, Sunil Kumar Barnwal highlighted how India’s digital public health architecture supports AI integration at scale. He referred to initiatives such as Ayushman Bharat Digital Mission, which provide an interoperable framework for integrated care delivery across the country.
According to Barnwal, when health systems embed AI-enabled diagnostics within such digital foundations, they can transition from reactive treatment to proactive risk identification. Consequently, policymakers gain access to structured, real-time data that strengthens monitoring, planning, and national-level decision-making.
From Technology Access to Sustained Deployment
As per the press release, Ankit Modi shifted the focus to a practical challenge: sustained deployment. He argued that health systems do not struggle with access to technology; rather, they struggle with embedding it into everyday workflows at scale.
When programmes integrate AI into routine screening processes, they enable continuous disease surveillance, early detection, and structured population-level screening. Moreover, integrated dashboards generate real-time insights, allowing authorities to proactively identify high-risk individuals and allocate resources efficiently.
Global Recognition and Public Health Relevance
Qure.ai has earned international recognition for its public health impact. It became the first Indian AI company recommended by the World Health Organization for autonomous tuberculosis screening.
Furthermore, national disease surveillance programmes in Malaysia, Thailand, El Salvador, and Colombia deploy its AI tools. These solutions operate across diverse care settings—from rural primary health centres to tertiary hospitals—demonstrating adaptability across infrastructure levels.
Drawing from this experience, Modi emphasized that embedding AI into routine diagnostic workflows delivers measurable clinical value. He noted that AI helps health systems manage workloads more efficiently, even in resource-constrained environments. Importantly, deployments at India’s scale illustrate how public health AI models can be replicated and adapted globally.
AI as Infrastructure, Not an Add-On
Throughout the session, panellists consistently reinforced a central theme: health systems must treat AI as infrastructure rather than as a standalone tool.
They stressed that collaboration among government institutions, public sector enterprises, academia, and technology providers ensures responsible implementation within regulatory frameworks. Such partnerships also promote accountability and long-term sustainability.
Ultimately, the discussion reflected growing confidence within Indian health systems to systematically evaluate and adopt validated AI solutions. By embedding AI into national programmes, stakeholders can transform disease detection, surveillance, and population health management at scale.