No longer confined to mapping, Geographic Information Systems (GIS) have evolved into a powerful analytical layer, enabling governments and enterprises to visualise, predict, and act with unprecedented precision. From targeted welfare delivery and urban infrastructure planning to supply chain optimisation and climate resilience, the geospatial turn is redefining how decisions are made at scale.
This transformation has been accelerated by recent policy reforms, particularly the liberalisation of geospatial data and the articulation of a national geospatial vision. The result is a rapidly expanding ecosystem where open data, satellite imagery, drones, and artificial intelligence are converging to create a new paradigm of location intelligence—one that is deeply embedded in India’s broader Digital Public Infrastructure.
In this context, Anoop Verma speaks with Agendra Kumar, Managing Director, Esri India Technologies Pvt. Ltd, on the evolution of India’s geospatial landscape, the growing synergy between GIS and AI, and the role of spatial intelligence in shaping the future of governance, infrastructure, and economic growth.
Edited excerpts:
India’s geospatial ecosystem has undergone a structural shift following the National Geospatial Policy. From your vantage point, how do you assess its impact on innovation, private sector participation, and data democratisation in India?
The introduction of the Geospatial Data Guidelines followed by the National Geospatial Policy has had a transformative impact on India’s geospatial ecosystem. One of the most significant shifts is the government’s recognition that GIS must play a role across nearly every sector of the economy. In fact, the government has identified multiple thematic areas where geospatial technologies are now considered indispensable.
Data availability, which was once a major constraint for government, private sector, and academia alike, has improved dramatically. The new guidelines have made it easier to access and share data, with a clear principle that data created using public funds should be made freely available. This has fundamentally altered the innovation landscape.
With greater data accessibility, organisations are now using geospatial datasets for diverse applications, including productivity enhancement and, increasingly, for training AI models. This was not anticipated earlier, but the rapid evolution of AI has made geospatial data a critical resource for GeoAI applications.
At Esri India, we have leveraged this opportunity by curating datasets from various government sources and making them available through our Living Atlas platform. Today, hundreds of data layers—covering everything from transport networks to agricultural and socio-economic indicators—are accessible and widely used. The scale of usage is reflected in the millions of requests we handle on our cloud infrastructure.
Additionally, reforms in drone regulations and remote sensing policies have significantly eased data collection processes. Satellite imagery is becoming more accessible, and with the rise of private satellite companies, data availability will only expand further. Overall, the changes have been profound, both in terms of data quality and quantity, and in enabling a more dynamic geospatial ecosystem.
You have often emphasised that GIS is no longer just about mapping but a powerful analytics layer. How is location intelligence transforming decision-making across sectors such as governance, infrastructure, and enterprise?
Location intelligence is fundamentally reshaping governance and service delivery. In welfare schemes, for instance, GIS enables precise identification of beneficiaries at the household level. This ensures that benefits reach the intended recipients—such as the senior-most woman in a family—while also ensuring that no one is left out.
In areas like property tax collection, GIS improves efficiency and transparency. Programs such as SVAMITVA have used geospatial technologies to provide property ownership records to rural households, empowering them economically.
Under the broader Digital India initiative, GIS is embedded in numerous applications developed in collaboration with institutions like NIC and the Registrar General of India. Whether it is property services, water and electricity billing, or urban governance systems, GIS is increasingly integral.
Urban administrations are also using GIS to enhance quality of life—through better sanitation systems, improved water distribution, efficient street lighting, and more responsive citizen services. The shift is from static mapping to dynamic, data-driven governance.
The convergence of GIS with AI, IoT, and digital twins is redefining spatial intelligence. How is Esri India operationalising GeoAI and real-time spatial analytics for large-scale applications?
GeoAI—essentially the integration of geography and artificial intelligence—is gaining strong traction in India. We are supporting multiple customers in adopting GeoAI within their workflows.
There are several practical applications. In Uttarakhand, for example, GIS combined with AI has been used to detect encroachments on government land. In agriculture, utilities, and infrastructure sectors, AI-driven spatial analytics are being used for monitoring assets such as transmission lines, pipelines, and crop conditions.
At Esri India, we have established a dedicated competency centre for GIS and AI. While we initially envisioned a specialised team, AI adoption has expanded rapidly across the organisation. Today, many engineers are integrating AI into their workflows.
Our approach includes developing GeoAI models—some proprietary, others open-source—which are trained using Indian datasets. For instance, building detection models have been adapted to Indian conditions and made available through the Living Atlas.
We also see significant progress in AI assistants embedded within GIS platforms, enabling users to interact with systems using natural language. Looking ahead, agentic AI—where autonomous agents perform tasks—is emerging as the next frontier. Overall, AI is dramatically improving productivity and reducing development timelines for applications.
With India positioning AI as sovereign digital infrastructure, where does GIS fit within the Digital Public Infrastructure (DPI) framework?
The National Geospatial Policy outlines the concept of a Unified Geospatial Interface (UGI), which aims to make GIS more accessible across government and private sectors. This aligns closely with the broader DPI vision.
GIS plays a foundational role in enabling digital services. For example, utilities are using geospatial systems to manage increasingly complex energy networks, particularly with the integration of renewable energy sources.
We have worked extensively with organisations like NIC, which has developed platforms such as Bharat Maps—an important asset for building government applications. As more datasets become available through institutions like the Survey of India, GIS will become an even more critical layer within DPI, supporting scalable, data-driven policymaking.
Could you share key case studies where GIS has delivered measurable governance outcomes?
There are numerous examples. Under the Smart Cities Mission, we have worked with around 50 cities. Cities like Varanasi and Chandigarh have implemented impactful applications in waste management, parking, street lighting, and water distribution.
The Brihanmumbai Municipal Corporation (BMC) is one of the most advanced users of GIS, leveraging it for solid waste management, building approvals, and water services. Citizens can report issues through applications, making governance more responsive.
Other urban bodies such as GMDA, HMDA, and Chennai’s municipal corporation are also adopting GIS to address challenges like urban flooding and infrastructure planning. While each city is at a different stage, the adoption of GIS is clearly improving urban governance outcomes.
How do you see the role of remote sensing and GIS integration evolving in sectors like agriculture, climate monitoring, and disaster resilience?
Solutions like Bharat ENVI are making advanced satellite analytics more accessible. ENVI enables sophisticated processing of satellite imagery, which can then be integrated into GIS platforms for decision-making.
In agriculture, for example, satellite data can be used for yield estimation at scale. Haryana has implemented a system where crop data—derived from both satellite imagery and field inputs—is used to streamline procurement. Farmers are assigned specific times to sell their produce, eliminating delays and ensuring direct payment into their bank accounts.
Similarly, satellite and drone data are increasingly used by insurance companies to assess crop damage due to natural disasters, enabling faster compensation. These applications demonstrate how remote sensing and GIS together can drive efficiency, transparency, and resilience across sectors.
What are the next frontiers for GIS-enabled urban digital twins in Indian cities?
Urban development is increasingly integrating GIS with Building Information Modelling (BIM), a combination often referred to as GeoBIM. This integration improves planning efficiency, reduces project delays, and can deliver significant cost savings.
Digital twins take this further by creating virtual representations of cities. These models enable planners to simulate development scenarios, optimise infrastructure, and improve urban resilience. Modern digital twins are built using high-resolution data collected through drones and aerial surveys, often achieving accuracy within a few centimetres. Advanced implementations also include underground mapping using ground-penetrating radar, which helps prevent repeated excavation of roads.
Cities like GIFT City have adopted forward-looking infrastructure models, including utility tunnels that simplify maintenance. These technologies collectively support more sustainable and efficient urban development.
How is Esri India helping enterprises build location-aware, resilient supply chains?
GIS enables enterprises to optimise logistics by integrating multiple datasets—road and rail networks, freight costs, weather conditions, and traffic patterns.
For example, companies can dynamically plan routes based on seasonal conditions such as monsoons, choosing between road and rail transport depending on cost and reliability. Retail and quick commerce companies rely heavily on GIS for delivery optimisation, using real-time data to determine serviceable areas and delivery times. In agriculture supply chains, GIS is used to balance supply and demand by guiding farmers on what to bring to markets, thereby stabilising prices.
Globally, organisations like DHL are already using advanced GIS-enabled logistics systems, including drone-based deliveries. These innovations are gradually shaping the future of supply chain management.
What interventions are needed to build an integrated national geospatial data ecosystem?
While data standards already exist—through bodies like the Open Geospatial Consortium—there is a need for greater convergence and alignment.
Technologically, interoperability is not a major challenge. Modern GIS platforms support open standards and can integrate seamlessly with enterprise systems such as SAP, Oracle, and Salesforce. Data from drones, IoT devices, and other sources can also be easily incorporated.
The focus should therefore be on continued standardisation efforts and policy coordination. At the same time, data sovereignty remains important, even as certain datasets—such as global climate data—are shared openly for collective benefit.
How do you view India’s geospatial economy over the next decade, and what role will Esri India play?
India’s geospatial economy is currently estimated at around ₹50,000 crore and is expected to double by 2030. This includes data collection, satellite imagery, and associated services. India is already a major exporter of geospatial services, particularly in utilities and land management. Adoption within the country is also growing rapidly, with strong government support.
However, one area where India still lags is in developing globally competitive geospatial products. While service capabilities are strong, product innovation requires scale and global markets. At Esri India, we are contributing through localisation efforts such as Indo ArcGIS, which integrates Indian datasets and solution templates tailored to local needs. We are also developing AI models and applications suited to Indian conditions and promoting reuse of solutions across states.
Our approach is to build an ecosystem—working with partners, enabling data access, and driving innovation—so that the entire geospatial sector in India can grow collectively.
