The exponential growth of Artificial Intelligence is driving a dual environmental crisis. Global data center electricity consumption is projected to surpass 1,000 TWh by 2030, more than doubling 2022 levels. This surge in energy demand is paired with an unsustainable thirst for water.
Training a single large language model can consume hundreds of thousands of liters of freshwater for cooling. As generative AI models proliferate, their annual water consumption is projected to reach between 700 and 1,100 million cubic meters by 2030. This consumption is unsustainable and presents a material risk to operations in water-stressed regions.
Traditional air cooling, the standard for decades, is obsolete for high-density AI workloads. Modern GPUs generate immense heat that air cannot efficiently dissipate. Liquid cooling (including direct-to-chip and immersion) is now an essential technology, not a luxury.
By using liquid, which has a much higher heat capacity, these systems can cut cooling energy by over 40% and lower the total Power Usage Effectiveness (PUE) by 15%. Critically, this technology enables closed-loop, water-neutral systems, eliminating reliance on evaporative cooling towers and solving the AI water crisis.
Sustainability is no longer a cost center; it is a primary driver of profitability and competitive advantage. Green data centers, by design, can achieve over a 50% reduction in operational expenditure (Opex) through massive energy savings.
For investors, integrating ESG is no longer optional. It is key to de-risking long-term assets, attracting top-tier clients who have their own ESG mandates, and meeting the stringent demands of global capital partners.
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