{"id":107050,"date":"2025-05-19T14:54:44","date_gmt":"2025-05-19T12:54:44","guid":{"rendered":"https:\/\/www.sonnenseite.com\/?p=107050"},"modified":"2025-05-19T14:54:44","modified_gmt":"2025-05-19T12:54:44","slug":"ai-at-the-expense-of-climate-protection-energy-requirements-of-data-centres-will-double-by-2030","status":"publish","type":"post","link":"https:\/\/www.sonnenseite.com\/en\/energy\/ai-at-the-expense-of-climate-protection-energy-requirements-of-data-centres-will-double-by-2030\/","title":{"rendered":"AI at the expense of climate protection: energy requirements of data centres will double by 2030"},"content":{"rendered":"\n

The use of artificial intelligence (AI) is currently growing rapidly. This growth is accompanied by an increasing energy demand, rising greenhouse gas emissions and higher water and resource consumption. <\/p>\n\n\n\n

On behalf of Greenpeace Germany, Oeko-Institut has analysed the environmental impact of artificial intelligence and prepared a trend analysis for up to 2030. This report shows the ways in which AI can become more sustainable and formulates policy options for reducing its harmful environmental impact.<\/p>\n\n\n\n

AI data centres drive consumption<\/h4>\n\n\n\n

As the use of AI increases, digital infrastructures \u2013 especially AI-specific data centres \u2013 are expanded. According to forecasts, the global electricity consumption of AI data centres will increase eleven-fold from the reference year of 2023 to 2030: from 50 billion kilowatt hours to around 550 billion kilowatt hours. Along with the other data centres, this means that around 1,400 billion kilowatt hours of electricity will be used for central data processing in 2030.<\/p>\n\n\n\n

This is associated with an increase in greenhouse gas emissions from data centres from 212 million tonnes in 2023 to 355 million tonnes in 2030, despite the assumed expansion of the use of renewable energies for electricity production.<\/p>\n\n\n\n

Other environmental burdens include the water required for cooling, which will almost quadruple to 664 billion litres, and the additional electronic waste generated by the expansion of data centres and AI capacity, which will amount to up to 5 million tonnes, over the same period. In addition, 920 kilotonnes of steel and around one hundred kilotonnes of critical raw materials will be required.<\/p>\n\n\n\n

Renewable energies do not cover estimated demand<\/h4>\n\n\n\n

With the rising demand for energy, local power grids are increasingly reaching their limits. The result, says Jens Gr\u00f6ger, Research Coordinator for Sustainable Digital Infrastructures at Oeko-Institut, is that \u2018in the years ahead, data centres will continue to rely on fossil fuels such as natural gas and coal \u2013 with correspondingly high environmental costs.\u2019 The major technology companies are also investing in nuclear power plants and small modular reactors (SMRs).<\/p>\n\n\n\n

Indirect effects of AI cannot be neglected<\/h4>\n\n\n\n

In addition to the so-called \u2018direct\u2019 environmental impacts \u2013 greenhouse gas emissions from data centres, water consumption for cooling systems and the use of resources in hardware production \u2013 the report also highlights the environmental significance of the indirect and systemic effects of AI. It can already be observed that AI is being used to accelerate environmentally harmful business practices. For example, AI tools are being used to tap into new fossil energy sources faster and more effectively, to increase the intensification of monocultures and to further increase private consumption. At the same time, negative environmental effects can also arise unintentionally due to errors in the data basis, incorrect training, or the operation of AI systems. Such indirect effects are environmentally significant but have rarely been recognised and discussed to date.<\/p>\n\n\n\n

Policy recommendations: to enshrine environmental risks in law and counteract them<\/h4>\n\n\n\n

To counter the risks, the study recommends the following measures at a policy level:<\/strong><\/p>\n\n\n

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