In New Delhi, the first India Artificial Intelligence (AI) Impact Summit has brought together governments, technology firms, multilateral agencies, and innovators to examine how AI can benefit people, the planet, and inclusive progress. Anchored in the Global South, the gathering signals a shift from receiving norms to shaping them. This matters because the next billion people will come of age in Asia and Africa, whose economies, public services, and climate resilience will be built alongside, or locked into, AI systems being designed and deployed today.
India has an opportunity to model its own path. But there is a tension that this summit has made plain: AI requires vast resources. A single hyperscale facility can draw as much electricity as an aluminium smelter. In 2024, India’s data centres consumed an estimated 150 billion litres of water. By 2030, that figure will more than double. According to recent analysis by the Council on Energy, Environment and Water (CEEW) and SYSTEMIQ, only five of 15 current state-level data centre policies embed sustainability provisions. Yet, resource intensiveness is only half the story. The deeper risk is that infrastructure built without foresight erodes the very thing expansion requires — social licence. The land-water-energy nexus compounds these pressures in ways that isolated metrics cannot capture. India’s blueprint for AI must, therefore, be not only efficient but co-owned: By states, utilities, and the communities that host it.
The summit also makes clear that AI is one of our most powerful tools for climate action. It optimises grids to absorb more renewable energy, forecasts floods with hyperlocal precision, monitors methane leaks, and strengthens agricultural resilience. This columnist chaired the AI and Climate Expert Engagement Group for the summit. Analysis by CEEW and Dalberg and insights from more than 20 global experts examined this duality across four layers — models, infrastructure, governance, and ecosystem. The expert group’s findings are unequivocal: AI ambition and climate responsibility is a false binary. It only appears real when we treat the two as separate portfolios, managed by different ministries, funded from separate budgets and investment vehicles, and thought about by segregated leadership clusters.
Therein also lies the opportunity. A country with 18% of the world’s population and 4% of its water should not have to afford the model of AI now scaling in less-stressed geographies. We must build something else. Call it frugal, even Gandhian, AI — fit-for-purpose, resource-efficient, and aligned with public purpose from the start. Consider what is already underway. India’s installed data centre capacity has nearly tripled since 2020, with committed investments exceeding $95 billion. The IndiaAI Mission is advancing application-led, socially responsive deployment. Digital public infrastructure demonstrates that population-scale systems can be open, interoperable, and oriented toward delivering public goods.
Scaling this momentum requires four shifts.
First, embed environmental accountability into the core governance of AI systems. India should bring in site-level disclosure of power usage effectiveness, water-use effectiveness, and carbon intensity — verified, not just self-reported. The EU AI Act now requires foundation model providers to document training data and capabilities. India should go further: Require similar disclosure for environmental footprints, and create an AI Energy and Water Star rating system that allows developers, enterprises, and governments to choose efficient models. If a consumer can know the energy cost of a refrigerator, a policymaker should know the water cost of a large language model.
Second, align infrastructure with resource realities. Our analysis of 15 state policies shows that incentives currently reward investment volume rather than performance. Rajasthan’s 2025 policy is the exception — mandating zero liquid discharge, rainwater harvesting, and green building standards. This should become the template everywhere. We need integrated spatial planning that evaluates grid capacity, water stress, and climate risk before land is allocated.
Third, treat climate-relevant data as digital public infrastructure. India’s Energy Stack and AgriStack demonstrate what is possible when data plumbing is fixed before applications are built. The same logic applies to climate. We need open, interoperable datasets on soil moisture, groundwater, wind patterns, and extreme-event impacts — governed by data trusts and accessible to verified public-interest AI applications. Satellite launches have increased by roughly 45% year-on-year over the past five years, much faster than our capacity to convert pixels into policy. AI can bridge that gap, but only if the underlying data is treated as a public good rather than a commercial asset. It is also how we assert data sovereignty. The Global South cannot remain a source of raw data and a market for finished models; we must capture value at home.
Fourth, reskill at scale and with precision. CEEW analysis has identified 36 emerging green value chains — circular economy, bio-economy, energy transition — that can employ 48 million people by 2047 and unlock $1.1 trillion in market value. Those jobs will not materialise automatically. They require skills taxonomies that connect worker competencies to employer demand, personalised learning pathways, and institutional ownership within public systems. AI can enable this matching. It cannot substitute for the political choice to invest in it.
When the summit closes, the harder work begins — translating principles into urgent strategies, procurement guidelines and disclosures into statutes, pilots into systems that outlast political cycles, and delivering for those who will inherit both the technology and the planet. India has done this before. Both the International Solar Alliance and the Coalition for Disaster Resilient Infrastructure began here as ideas. The Green Development Pact was negotiated in New Delhi. Each time, we refused the false choice between growth and sustainability. Each time, we built coalitions of the doing.
India now has an opportunity to show the world that the most powerful technology of our time need not come at the cost of the planet. We must build not just AI agents but invest in the human agency to exercise our choice.
Arunabha Ghosh is CEO, the Council on Energy, Environment and Water (CEEW). The views expressed are personal
