At the India AI Impact Summit 2026, the conversation around data took center stage in the session “Data Sharing Infrastructures for AI: Building for Trust, Purpose, and Public Values.” The panel underscored that while artificial intelligence thrives on data availability, the frameworks that govern how data is shared, protected, and monetized will ultimately decide whether AI advances public good or deepens inequity.
Defining Data as Digital Public Infrastructure
Moderated by Astha Kapoor (Aapti Institute), the discussion brought together Chenai Chair (Masakhane Language Hub), Rahul Matthan (Trilegal), Saranya Gopinath (RazorPay), and Vijay Suresh Kumar (Gates Foundation). The panel explored the idea of treating data as a form of digital public infrastructure (DPI)—open enough to enable innovation, yet protected enough to ensure individual agency and public trust.
Participants noted that current data-sharing ecosystems are fragmented and often skewed in favor of technology platforms that extract significantly more value than the creators, curators, or small organizations that host the data. This imbalance has led to both economic and ethical tensions between data creators and data extractors, prompting questions around who genuinely benefits from AI-driven insights and commercial applications.
Balancing Openness and Accountability
The speakers agreed that open data must be accompanied by constructs of purpose, consent, and provenance. A model of shared stewardship—where data layers are standardized and usage is verifiable—can help align innovation with societal interests. One viewpoint suggested that the very friction between value extractors and data stewards might not be entirely negative; these tensions drive negotiation, transparency, and fresh thinking toward equitable frameworks.
Towards a Purpose-Driven Ecosystem
As the session concluded, the message was clear: the future of AI innovation depends on designing trustworthy data infrastructures that prioritize public values as much as economic opportunity. Collaboration among regulators, technologists, and civic organizations will be crucial to ensure that data as DPI serves collective benefit rather than concentrated control.
