New Delhi: Open networks and digital public infrastructure took centre stage at the India AI Impact Summit 2026, where experts discussed how these frameworks can help scale artificial intelligence across sectors.
During the session titled “AI and Open Networks: Creating Impact at Scale,” speakers argued that breakthroughs in AI models alone will not ensure impact. Instead, they said widespread adoption depends on interoperable platforms, consent-based data systems and inclusive digital ecosystems.
The panel featured industry and global leaders, including Nandan Nilekani, Kiran Mazumdar-Shaw, Sangbu Kim, Sunil Wadhwani and James Manyika. Together, they explored how open platforms can move AI from pilot projects to population-scale deployment in healthcare, agriculture and public services.
Nandan Nilekani highlighted AI as a general-purpose technology and stressed rapid diffusion for public benefit. Drawing parallels with UPI’s architecture, he said open systems allow innovators to build applications at the edge. As a result, users experience simpler and more accessible services.
Kiran Mazumdar-Shaw focused on healthcare transformation. She noted that India’s digital health stack, combined with AI, could create a global reference model. Moreover, she emphasised the goal of delivering universal health coverage sustainably and at scale.
Open networks and digital public infrastructure enable inclusive AI models
Sangbu Kim from the World Bank underlined the importance of replicable frameworks. He said policymakers must identify which elements can transfer across countries. Therefore, lessons from India’s experience could guide global adaptation.
Sunil Wadhwani described digital public infrastructure as the backbone of scalable AI in the social sector. Without reliable data pipelines and interoperable systems, he said, large-scale deployment would remain limited.
James Manyika placed the discussion in a global innovation context. He stressed that broad access to AI expands opportunity and strengthens innovation capacity worldwide.
The session concluded that affordable inference, multilingual interfaces and plug-and-play innovation frameworks are essential for inclusive growth. By combining institutional trust with technological openness, countries can transform AI into a shared development capability rather than a concentrated advantage.
