As AI systems begin to shape planning, targeting, grievance handling, and service delivery, the institutions that work closest to communities will help ensure that data reflects lived reality rather than only recorded reality
India’s next governance leap may not solely come from digitisation. It will come from making public systems more intelligent, more adaptive, and more responsive to the dynamics at the grassroots. That opportunity is especially significant at the panchayat level, where governance is not an abstract policy but an everyday interface between the state and citizens.
The scale is already formidable. As of FY 2025–26, India had 2,64,211 gram panchayats and equivalent bodies, while Direct Benefit Transfer (DBT) systems had cumulatively transferred Rs. 49,88,905 crore, including Rs. 6,23,424 crore in FY 2025–26 alone, across 325 schemes run by 56 ministries. This is no longer a question of whether India has digital governance infrastructure. It is a question of how intelligently that infrastructure can now evolve.
That is where Artificial Intelligence comes in the picture. NITI Aayog’s national AI strategy identified healthcare, agriculture, education, smart mobility, and smart cities as priority sectors, while its later Responsible AI paper cited estimates that data and AI could add USD 450–500 billion to India’s economy by 2025.
More recent work from NITI Aayog projects that accelerated AI adoption could contribute USD 500–600 billion over and above India’s current GDP growth by 2035. International institutions have echoed the opportunity, but with an important caveat: UNDP notes that AI can make public services more responsive and efficient, while the World Bank has warned that the benefits will depend on whether countries build the right skills, infrastructure, and institutional capacity around these systems.
From Digital Reach to Intelligent Delivery
India has already begun laying the rails for this transition. As of 11 March 2026, 2,54,604 gram panchayats, or 96.36 percent of the national total, had uploaded their gram panchayat development plans on eGramSwaraj. By the end of March, Panchayati Raj Institutions had transferred Rs. 53,342 crore through the eGramSwaraj-PFMS interface, while 2,55,254 gram panchayats had prepared and uploaded plans for FY 2025–26.
This matters because once planning, accounting, and payments move onto interoperable digital systems, governance gains a usable data layer. The next step is to turn that data layer into a decision layer.
That shift is no longer mere conceptual. In agriculture, government-backed AI initiatives already point to the direction of travel. NITI Aayog and IBM’s crop-yield prediction initiative was designed for aspirational districts across Assam, Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan, and Uttar Pradesh.
The National Pest Surveillance System now supports 66 crops and more than 432 pest types, providing real-time advisories to over 10,000 extension workers. Kisan e-Mitra, the Ministry of Agriculture’s AI-enabled assistant, had answered more than 93 lakh queries by December 2025 in 11 regional languages, while the Digital Agriculture Mission had created over 7.63 crore Farmer IDs and surveyed 23.5 crore crop plots. These are early signals of what AI-enabled public administration can look like when it is tied to specific delivery problems.
The Panchayati Raj system is also beginning to see direct AI applications. In August 2025, the Ministry of Panchayati Raj launched SabhaSaar, an AI-powered tool that converts gram sabha and panchayat meeting audio and video into structured minutes. By March 2026, the ministry had expanded SabhaSaar to more than 20 languages, signalling that AI at the grassroots need not begin with grand claims; it can begin by reducing friction in routine governance and improving the quality, speed, and consistency of local records.
Making the Last Mile Smarter
Yet the future of intelligent governance will depend on whether AI remains grounded in local realities. Panchayats are not just administrative nodes; they are social institutions. India has approximately 31 lakh elected representatives in local governments, including about 14.5 lakh women, or roughly 46 percent of the total. More than 21 states have already moved to 50 percent reservation for women in Panchayati Raj Institutions.
That scale of embedded, local representation is a governance asset in its own right. It means the last mile can become not just a site of implementation, but a source of intelligence, feedback, and course correction.
This is where grassroots organisations matter. As AI systems begin to shape planning, targeting, grievance handling, and service delivery, the institutions that work closest to communities will help ensure that data reflects lived reality rather than only recorded reality. In sectors like education, healthcare, and skilling, the value of social organisations is not only that they deliver programmes, but that they generate grounded insight, community trust, and implementation support that public systems can build upon. The future, then, is not simply one of more technology in governance. It is one of better alignment between digital systems, local institutions, and community realities. India already has the scale, the digital rails, and the early AI use cases.
The next generation of panchayati governance will be defined by how well it can combine those strengths, so that the move from digital to intelligent also becomes a move towards more inclusive, more contextual, and more effective last-mile delivery.
Santanu Mishra, an IIM-Ahmedabad alumnus and an ICSI associate member, is a co-founder of Smile Foundation, an organisation working in the area of child education, skilling of youth and community healthcare.
