AI can reshape environmental governance

As India confronts growing challenges of water stress, climate change and rapid urbanisation, AI can become a powerful instrument for integrating environmental data, anticipating risks and strengthening governance itself

Artificial intelligence is rapidly becoming central to India’s development story. Through the IndiaAI Mission and investments in digital infrastructure, data centres and advanced computing, India has made clear its ambition to become a global AI leader.

Increasingly, the national conversation has moved beyond AI models and computing power to how AI can strengthen institutions, improve productivity and address real-world development challenges. Yet one important area has received relatively little attention: environmental governance.

This deserves greater focus because environmental governance sits at the intersection of economic growth, climate resilience and public welfare. Decisions on water, agriculture, infrastructure, urbanisation and disaster preparedness increasingly shape India’s long-term development trajectory. As environmental risks become economic risks, the quality of environmental governance will increasingly influence the quality of growth itself.

Much of the public debate on AI has focused on its environmental footprint, particularly the energy and water needed to support computing infrastructure. Those concerns are legitimate and deserve attention. But they capture only one side of the story.

An equally important question is how AI can strengthen governments’ ability to understand and manage the natural systems on which development depends.

Environmental governance has long faced a challenge not of data scarcity but of data integration. India today generates enormous amounts of information on rainfall, rivers, groundwater, weather, land use and ecosystems. The challenge has been bringing these different streams of information together in ways that support timely public decisions. Valuable information exists, but it often remains fragmented across institutions and programmes.

Today, advances in satellite imagery, geospatial technologies, sensor networks, cloud computing and AI make it possible to analyse multiple environmental datasets simultaneously, identify patterns that would otherwise remain hidden and generate more timely insights for decision-making. This is more than better monitoring. It enables governments to anticipate risks, understand how different systems interact and respond before problems become crises.

Water offers perhaps the clearest illustration. India is home to nearly 18 per cent of the world’s population but has only around 4 per cent of its freshwater resources. Groundwater acts as a critical buffer against monsoon variability, supporting more than 60 per cent of irrigation and around 85 per cent of rural drinking water. As climate variability increases, managing this resource is becoming more complex.

Yet decisions relating to river basins, groundwater, irrigation, urban water supply and disaster management are often informed by separate datasets, institutions and planning processes, even though water does not recognise administrative boundaries.

Integrating satellite imagery from ISRO, hydrological observations under the National Hydrology Project, groundwater assessments by the Central Ground Water Board, weather forecasts, reservoir operations and water quality monitoring into shared decision-support systems would enable policymakers to understand how river basins are evolving and intervene earlier.

Water is only one example. The same approach can strengthen air quality management, improve pollution surveillance, support ecosystem monitoring and help governments respond earlier to emerging environmental risks. Better environmental intelligence is therefore not simply an environmental objective; it increasingly shapes decisions on agriculture, infrastructure, industrial investment, urban planning and disaster resilience.

India is not starting from scratch. Platforms such as India-WRIS, the National Hydrology Project and PARIVESH have already demonstrated how digital technologies can strengthen environmental governance. The next step is to connect these capabilities rather than continue developing them in isolation.

There is a useful lesson here from India’s Digital Public Infrastructure. Its success came from creating shared standards and trusted digital systems on which governments, businesses and innovators could build. Environmental governance requires a similar approach. Shared environmental data, common standards and secure data-sharing can help institutions work from a shared understanding of environmental conditions rather than fragmented information.

At its core, governance is about making decisions under conditions of uncertainty. Technology cannot eliminate that uncertainty, but it can reduce it.

The real value of AI lies not in replacing human judgement but in helping governments understand emerging risks earlier, see connections more clearly and make better-informed decisions. Data quality, institutional capacity and collaboration across government remain indispensable.

As India builds its AI ecosystem, environmental governance should be recognised as one of its priority public-sector applications. A practical starting point would be AI-enabled pilot projects in selected river basins, integrating hydrological, groundwater, meteorological and geospatial datasets into shared decision-support systems. Building on existing platforms rather than creating new institutions would demonstrate how AI can improve public decision-making and generate lessons for other sectors and states.

India has rightly set itself the ambition of becoming a global AI leader. But leadership will ultimately be measured by more than the sophistication of models or the scale of computing infrastructure. It will also depend on how effectively AI is applied to solve real public challenges.

India’s first digital revolution transformed public service delivery. Its next has the opportunity to strengthen the quality of public decision-making itself. If AI helps governments better understand and manage water, air and other natural systems with greater foresight, it will not only improve environmental outcomes. It will demonstrate that AI creates its greatest public value when it helps governments govern better.

The real value of AI lies not in replacing human judgement but in helping governments understand emerging risks earlier, see connections more clearly and make better-informed decisions. Data quality, institutional capacity and collaboration across government remain indispensable

Leena Nandan is Former Secretary, Ministry of Environment, Forest and Climate Change, and Distinguished Fellow, Earth Science and Climate Change, TERI. Suryaprabha Sadasivan is Managing Principal, Chase Advisors; Views presented are personal.