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The hidden costs of AI: Unpacking its energy and water footprint

On 12 February 2025, the OECD and IEEE co-organised an event on the margin of the French AI Action Summit with diverse experts to discuss AI’s growing environmental challenges. The event’s three main sessions covered critical sustainability concerns: the environmental cost of inference, the impact of data centres on the electricity grid, and AI’s water footprint.

AI Water Usage Panel Discussion
AI environmental impact extends beyond energy consumption to include natural resource use—specifically, water. AI technologies, particularly those relying on large-scale data processing and cloud computing, require significant amounts of water for cooling purposes in data centres. As the demand for AI-powered services grows, so does the pressure on water resources, particularly in regions already facing water scarcity. The challenge lies in balancing the benefits of AI with the responsible management of water resources, ensuring that the technology’s potential for innovation doesn’t come at the cost of sustainability.  

Guiding questions:
• How significant is water consumption in AI-related infrastructure, especially in data centres, and how does it compare to other industries regarding resource use?
• What are some innovative cooling technologies that can help reduce water usage in AI data centres, and how feasible are they to implement at scale?
• How can the AI industry collaborate with local communities and governments to ensure that AI deployment doesn’t exacerbate regional water challenges?
• What role can policymakers play in setting regulations or incentives that encourage water-efficient practices in the development and operation of AI infrastructure?
• Are there examples where AI companies have successfully minimized their water usage, and what can others learn from these practices?  

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October 23

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