Why India needs better local data for smarter policies?

Technology use and use of artificial intelligence can answer several questions and help tackle challenges. Solutions lie in some of the successfully implemented projects.

India’s economy is growing fast, and its digital transformation is setting an example for the world. The country has already registered over 1.38 billion people on Aadhaar, enabling seamless digital governance [1]. With ambitious initiatives like Digital India and Aadhaar, the country is making significant strides in governance and service delivery. However, to fully harness this growth, policies must be backed by accurate, real-time local data.While national statistics provide an overview, ground realities vary significantly across states and districts. Hence, strengthening India’s data infrastructure will ensure that policies are more targeted, inclusive, and effective.

However, the path to achieve a responsive infrastructure may not be an easy one. One key challenge is the reliance on outdated or broadly averaged data, making it difficult to address specific regional issues. Labour market policies, for instance, are based on periodic surveys, but employment conditions change rapidly, especially in cities and the informal sector.

A few examples highlight the problem. Launched in 2023, Karnataka's Skill Connect Portal, provides real-time tracking of employment trends across districts. The platform integrates job listings, employer demands, and skill training programs, offering insights into labour market shifts, particularly in the informal sector [2]. National averages do not reflect local economic diversity. A policy that works well in Bengaluru’s IT industry may not be suitable for Bihar’s agriculture-based economy.

Gujarat utilized the PM Gati Shakti National Master Plan to streamline the planning of its 300 km coastal corridor, leveraging district-level economic indicators to align infrastructure development with regional workforce capabilities and economic needs. This reduced the number of NoC permissions required for clearance from 28 to 13, enhancing connectivity between four districts and boosting tourism [3]. The Economic Survey 2023 has recognized the need for high-frequency district-level indicators, and efforts are underway to bridge this gap.

An area where improved local data can make a significant impact is job creation. Without real-time, localized employment data, policies may miss addressing job demand in specific areas. The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) has successfully provided work to millions, but a lack of real-time labour migration data sometimes leads to uneven job distribution.

Public welfare and social schemes have also seen great progress but can be further optimized with better data. Many programs still rely on outdated census figures, causing delays and exclusion errors. During COVID-19, rapid digital initiatives like the PM Garib Kalyan Yojana helped millions, but many migrant workers struggled due to gaps in real-time tracking.

The solution

Technology offers a clear path forward. Artificial intelligence (AI) and big data analytics can modernize data collection and policymaking, ensuring that resources are allocated efficiently.It helps identify trends, predict outcomes, and optimize resource allocation, ultimately improving the efficiency and fairness of policies. There are score of successful examples on this.

Punjab's Remote Sensing Centre (PRSC) uses AI and GIS to monitor crop health, optimize irrigation, and reduce pesticide use, helping farmers make data-driven decisions. This initiative integrates satellite imagery with real-time farm data to optimise soil health assessment, water management, and crop productivity, helping farmers make data-driven decisions [4].The Aadhaar and UPI ecosystems have demonstrated India’s ability to manage large-scale digital data collection, which can now be expanded to economic and labour statistics. The ‘Bhashini’ project, which uses AI for language-based data collection, could also be adapted for district-level economic surveys.

To build a stronger data-driven policy framework, India must focus on decentralised, technology-backed data collection at the district and panchayat levels. Implementing AI-driven economic dashboards, like Estonia’s e-Governance model, can enhance real-time decision-making. Collaboration between government agencies, private sector players, and research institutions will be key to ensuring data accuracy and usage. For example, the National Data Governance Policy (NDGP) aims to streamline data-sharing and improve interoperability between different government departments. Case studies from Telangana and Karnataka show that state-led data platforms can significantly improve governance outcomes.

Uttar Pradesh has already taken the lead by estimating District Domestic Product (DDP) for its 75 districts, offering a model for other states to follow. [5] Similarly, Telangana’s Open Data Portal has demonstrated how regular monthly updates enhance decision-making and transparency, showcasing the benefits of granular, real-time data for governance [6]. With India’s expanding digital infrastructure, the feasibility of implementing nationwide AI-driven economic dashboards is increasing.

India’s digital economy is set to contribute nearly 20% of national income by 2029-30, outpacing agriculture and manufacturing. In 2022-23, it accounted for INR 31.64 lakh crore (US$402bn) and employed 14.67 million workers [7]. To capitalise on this shift, India must strengthen its local data ecosystem, integrating AI-driven analytics with platforms like PM Gati Shakti and expanding district-level data systems. With the right steps, India can emerge as a global leader in data-driven governance, making policies more efficient, inclusive, and future-ready.