{
  "id": 1295009,
  "title": "Should India make AI pay back its water debt?",
  "url": "https://urgent.news/2026/08/16/should-india-make-ai-pay-back-its-water-debt",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-16T15:18:28.000Z",
  "source": {
    "name": "The Economic Times",
    "slug": "the-economic-times",
    "url": "https://economictimes.indiatimes.com/ai/ai-insights/when-the-cloud-gets-thirsty-should-india-make-ai-pay-back-its-water-debt/articleshow/133277452.cms"
  },
  "original_language": "en",
  "account": "India faces a dilemma as it expands its artificial intelligence infrastructure, a critical component of its digital economy. While AI brings economic benefits, its underlying infrastructure of data centres has a significant environmental impact. These data centres consume vast amounts of electricity and water, raising concerns about resource depletion, especially in water-stressed regions. The International Energy Agency estimates global data centre electricity consumption at 415 terawatt-hours in 2024, while India's data centres used around 150 billion litres of water in 2025, a number expected to double by 2030. Projections suggest that global AI-related water withdrawals could reach 4.2-6.6 billion cubic metres annually by 2027. This water footprint is a critical issue, as AI infrastructure can be situated in areas where water is already scarce. The challenge lies in balancing India's digital ambitions with environmental sustainability. Water credits, a concept similar to carbon credits, could potentially address this issue. However, unlike carbon credits, water credits must be carefully designed to reflect the local nature of water resources. A hierarchy of measures—avoiding water use, reducing consumption, reusing water, replenishing water sources, and compensating for unavoidable water use—is proposed. This framework should include stringent requirements for facilities in water-stressed areas, such as using treated wastewater, closed-loop cooling systems, and water-efficient cooling technologies. Environmental approvals for major data centres should involve basin-level water assessments. Only then should companies be eligible for water credits, which could finance various water restoration projects. Such credits must be based on rigorous methodologies, ensuring additionality, water quality, ecological restoration, and community benefit. The social dimension is also crucial, as AI's environmental burdens may disproportionately affect vulnerable communities. Ultimately, the aim should be to integrate resource efficiency into India's competitive advantage, making AI infrastructure sustainable without compromising the country's water resources.",
  "summary": null,
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}