This project is generously supported by the M.S. Chadha Center for Global India (CGI) at Princeton University.
Project Overview
In recent years, India has drawn global attention for its Digital Public Infrastructure (DPI)—a set of open, interoperable systems that have reshaped how citizens access services, businesses innovate, and governments deliver at scale. The massive adoption of India’s DPI has become a model for other countries, especially in the Global South.
More recently, India has also awoken to the tremendous potential (but also risks) of Artificial Intelligence (AI). The February 2026 AI Impact Summit in New Delhi presents what may be a distinctive approach to AI—one that builds on India’s DPI experience, emphasizing the importance of openness, inclusion, and public purpose.
This project, funded by the M.S. Chadha Center for Global India (CGI) at Princeton University, examines the emerging intersections between DPI and AI. It explores how these two domains are evolving in India and—consistent with CGI’s global focus—across the world.
Three Strands
AI and DPI Integrations
This strand investigates how AI is being embedded within DPI, and what possible opportunities and risks this poses. We examine AI as an enhancement of DPI (AI for DPI), DPI as a source of data for AI (DPI for AI), and AI as a core infrastructural layer of DPI (AI as DPI). We also seek to foster convergences with the "public AI” conversation that has predominantly taken place in the West.
The Global DPI Landscape
This strand seeks to map the global diffusion and typologies of DPI, focusing especially on how India’s experience is informing other countries. Researchers have engaged with policymakers and stakeholders across India, Côte d’Ivoire, Rwanda, Trinidad and Tobago, and the broader Global South, identifying patterns of adaptation and local innovation.
Building an Evidence Base
While many claims are made about DPI’s benefits—and increasingly about the promise of DPI+AI—these have not been rigorously examined or tested. A growing body of evidence does exist but much of it remains fragmented and otherwise inaccessible. This strand aims to consolidate and systematize the emerging empirical base, bringing together existing studies and data in a coherent, accessible framework (e.g., a data or evidence dashboard). The broader goal is to move beyond advocacy toward a grounded, empirical understanding of what DPI and DPI+AI actually deliver, under what conditions, and for whom.
Project Team
The team brings together an inter-disciplinary set of interests and expertise, encompassing economics, policy, and technology.
