By Swati Meena Naik
Artificial intelligence has become the defining technological conversation of our time. Governments across the world are exploring chatbots, predictive analytics, digital assistants and decision support systems to improve public service delivery. Yet, much of the debate continues to focus on AI models and algorithms. The more fundamental question lies in the architecture of the public systems on which these technologies are expected to operate.
India’s experience with digital public infrastructure (DPI) has demonstrated the transformative power of foundational digital systems. Trusted digital identities and interoperable transaction platforms have enabled innovation at an unprecedented scale. This experience offers a wider lesson: once trusted identities and interpolable digital platforms are established, the next opportunity is to extend these design principles to sectoral public systems that continuously generate operational data and demand responsive, evidence-based governance.
Governments are investing heavily in infrastructure across drinking water, urban development, healthcare, agriculture, transport and energy. As these systems are planned, constructed, operated and maintained, millions of data points are generated every day through assets, operational transactions, inspections, citizen interactions and service outcomes. The challenge is no longer data generation, but converting this expanding information ecosystem into institutional intelligence.
For AI to become effective in governance, public systems must create trusted, connected and continuously evolving knowledge loops. Operational experience, citizen feedback, institutional reasoning, technical validation and verified outcomes should reinforce one another. Over time, these loops can help institutions learn, adapt and improve the quality of public services.
This requires a different approach to DPI design, where AI readiness is treated as a core principle rather than an afterthought. Digital identities, operational transactions, field observations and decision-making processes should not remain isolated datasets. Their value emerges when they are linked through interoperable digital architecture, allowing every transaction and interaction to strengthen the collective knowledge of the system.
The Jal Jeevan Mission offers an emerging illustration through the Sujalam Bharat Digital Public Infrastructure. The platform seeks to create digital identities for rural water infrastructure, map source-to-tap relationships, capture operational transactions and integrate functionality assessments with technical validation. As it evolves, it can also connect citizens, gram panchayats and frontline functionaries within a common ecosystem. Every intervention and validated outcome can further enrich the knowledge base and strengthen institutional learning.
One advantage often overlooked in discussions on AI is that governments already possess something many private organisations spend years trying to create. Every inspection, audit, field verification and review generates structured operational knowledge. The opportunity, therefore, lies less in collecting additional data than in connecting existing knowledge across institutions through interoperable digital systems.
None of this diminishes the importance of human judgement. AI is best understood as an institutional capability that helps identify patterns, anticipate emerging risks and convert fragmented operational information into timely, actionable intelligence.
AI is not the end of the story. Better public service delivery is. The true promise of AI-ready digital public Infrastructure lies in enabling public institutions to continuously learn, respond with greater precision and ultimately improve outcomes for the citizens they serve.
The writer is joint secretary, National Jal Jeevan Mission
Disclaimer: The views expressed are the author’s own and do not reflect the official policy or position of Financial Express.