**Executive Summary**
This document summarizes the "AI and Open Networks: Creating Impact at Scale" session at the India AI Impact Summit 2026. The discussion focused on the importance of digital public infrastructure (DPI) and open network architectures in scaling AI deployment, especially in healthcare, agriculture, and public services. The panel highlighted the need for affordable, easy-to-use, multilingual, inclusive, and replicable AI models for global impact.
**Key Points / Main Content**
* **Core Proposition:** The future of AI depends on both model breakthroughs and digital public infrastructure (DPI) and open network architectures.
* **India's Approach:** India's combination of consent-based data systems, interoperable platforms, and open participation has established a foundation for population-scale AI deployment.
* **Panelists' Insights:**
* **Nandan Nilekani:** Open networks accelerate productive AI diffusion; the key is diffusing AI's use productively.
* **Kiran Mazumdar-Shaw:** India can establish a global reference model for AI use in healthcare.
* **Sangbu Kim:** There's a need for replicable and scalable AI models across countries.
* **Sunil Wadhwani:** DPI is essential for scalable AI deployment in the social sector.
* **James Manyika:** Access to AI unlocks opportunities and expands innovation capacity.
* **Key Enablers for Scaling AI:** The session concluded that open networks and DPI create the necessary foundation to move AI from pilot projects to population-scale deployment through low-cost inference, multilingual access, and plug-and-play innovation frameworks.
**Impact Analysis**
**Global Population**
* **Impact:** Benefits from AI solutions in healthcare, agriculture, and public services through globally replicable AI models
* **Action Required:** Benefit from AI solutions and contribute to refining replicable AI models
**AI Innovators & Developers**
* **Impact:** Opportunity to build and deploy AI applications using open networks.
* **Action Required:** Develop and deploy AI applications within open network architectures.
**Governments & Policymakers**
* **Impact:** Opportunity to implement scalable and replicable AI models.
* **Action Required:** Implement DPI and establish open networks to support AI deployment.
**World Bank Group**
* **Impact:** Extends lessons from India to multiple regions to support replicable and scalable AI models.
* **Action Required:** Emphasise focus on the critical components that can be replicated across governments and countries.
**Healthcare Sector**
* **Impact:** Opportunity to deliver universal health coverage at scale in a sustainable way.
* **Action Required:** Focus on "universal health coverage delivered at scale in a sustainable way".
**Social Sector**
* **Impact:** Opportunity to deploy AI to the social sector.
* **Action Required:** Implement DPI to enable scaled deployment of AI in the social sector.
Key Entities Referenced
India AI Impact Summit 2026: A summit focused on scaling AI in various sectors through digital public infrastructure and open networks.
Digital Public Infrastructure (DPI): Refers to the digital systems and architectures essential for scalable AI deployment, particularly in sectors like healthcare and agriculture.
Ministry of Electronics & IT: The government ministry associated with the AI Impact Summit.
AI and Open Networks: Creating Impact at Scale: Session title and theme, emphasizing the importance of open networks for accelerating AI diffusion and productive use.
Ministry of Electronics & IT
Experts Discuss Role of Open Networks and
Digital Public Infrastructure in Scaling AI at India
AI Impact Summit 2026
Digital Public Infrastructure Seen as Key to Scaling AI in
Healthcare, Agriculture and Public Services
Leaders Call for Affordable, Easy-to-Use and Multilingual AI
for Wider Access
Panel Emphasises Need for Inclusive and Replicable AI
Models for Global Impact
Posted On: 20 FEB 2026 1:37PM by PIB Delhi
The session “AI and Open Networks: Creating Impact at Scale” at the India AI Impact Summit 2026 set
out a clear proposition: the future of AI will be determined not only by model breakthroughs, but by the
digital public infrastructure and open network architectures that allow innovation to reach millions of
people. Drawing on examples from healthcare, agriculture, science, and public service delivery, speakers
demonstrated how India’s approach, combining consent-based data systems, interoperable platforms and
open participation, has created the foundation for AI deployment at a population scale.
The session featured high-level discussions among Nandan Nilekani, Co-founder and Patron, Networks
for Humanity; Kiran Mazumdar-Shaw, Chairperson, Biocon Group; Sangbu Kim, Vice President for
Digital & AI, World Bank Group; Sunil Wadhwani, Founder, Wadhwani AI; and James Manyika,President, Research Labs, Technology & Society, Google & Alphabet, on how open networks and digital
public infrastructure can enable AI deployment at population scale. From low-cost agricultural advisories
and AI-enabled diagnostics to protein research and frontline service tools, the panel examined how
reducing inference costs, simplifying user experience through agent-based interfaces and enabling
multilingual access can turn AI into a mass-use technology rather than a specialist capability.
Nandan Nilekani, Co-founder and Patron, Networks for Humanity, underscored the importance of open
networks in accelerating productive AI diffusion. Highlighting AI as a general-purpose technology, he
said the real question is “what is the fastest way of diffusing its use in a productive way for people?”
Drawing parallels with UPI’s open architecture, he emphasised that “open networks allow many actors
and innovators to build applications at the edge using AI,” adding that “the real power of agents is
removing complexity for the user.”
Kiran Mazumdar Shaw, Chairperson, Biocon Group, emphasised the transformative opportunity at the
intersection of India’s digital health stack and AI. Highlighting the potential to build a global reference
model, she said India can “immediately create a global reference model when it comes to the use of AI
with the kind of health data we are connecting.” She added that the ultimate goal is “universal health
coverage delivered at scale in a sustainable way.”
Sangbu Kim, Vice President for Digital & AI, World Bank Group, stressed the need for replicable and
scalable models across countries. Emphasising global adaptability, he said the focus must be on “what
elements can be replicated across governments and countries, and what the critical components really
are,” noting that lessons from India are already being extended to multiple regions.
Sunil Wadhwani, Founder, Wadhwani AI, highlighted digital public infrastructure as the backbone of
scalable AI deployment in the social sector. Emphasising practicality, he said, “You simply cannot build
AI for the social sector without the kind of data and pipelines that DPI provides,” adding that without
such infrastructure, large-scale deployment “would never scale to the levels we are seeing today.”
James Manyika, President, Research Labs, Technology & Society, Google & Alphabet, placed the
discussion in a broader global innovation context. Highlighting the importance of access, he said, “access
to AI is essential to unlock opportunities and expand the innovation capacity for people everywhere,”
describing the pace of AI development as “an extraordinary opportunity to solve problems and empower
people.”
The session concluded that open networks and DPI together create the institutional and technological
foundation required to take AI from pilots to population-scale deployment. By combining low-cost
inference, multilingual access and plug-and-play innovation frameworks, countries can build systems that
are not only inclusive at home but also replicable across the globe, turning AI into a shared development
capability rather than a concentrated advantage.
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Mahesh Kumar/ Pawan Faujdar/ Navin Sreejith/ Anil Dutt Sharma
(Release ID: 2230663) Visitor Counter : 325
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