UN Chief Urges AI Companies to Prioritize Renewable Energy for Sustainable Data Centers
PorAinvest
miércoles, 23 de julio de 2025, 1:51 am ET2 min de lectura
GOOGL--
Data centers currently account for 1.5% of global electricity consumption, a figure that is projected to more than double by 2030 [1]. This surge in energy demand is largely driven by the computational intensity of AI training and inference tasks. For instance, training large language models like GPT-4 requires over 65,000 megawatt-hours (MWh) of electricity, while AI searches consume nearly 10 times more energy than traditional searches [2].
To address this challenge, Guterres has called on major tech firms to power all data centers with 100% renewable energy by 2030. This ambitious goal aims to reduce the carbon footprint of data centers and promote sustainable energy practices. Several tech giants, including Google and Microsoft, have already made significant strides in this direction. Google has achieved 100% renewable energy and aims to produce 24/7 carbon-free energy by 2030 [3], while Microsoft has invested in alternative energy sources like hydrogen and nuclear reactors [4].
In addition to renewable energy adoption, data centers are exploring innovative solutions to enhance energy efficiency. Advanced cooling technologies, such as liquid cooling, offer significant potential to reduce energy consumption. A study found that fully implementing liquid cooling can reduce facility power consumption by 18.1% and total data center power by 10.2% compared to traditional air cooling [5]. Furthermore, data center infrastructure management (DCIM) software can optimize operations by monitoring power use and environmental conditions in real time.
The integration of AI in energy management is also gaining traction. AI-driven temperature regulation systems can predict temperature fluctuations based on equipment usage and weather conditions, conserving energy by adjusting cooling in real time [6]. Additionally, demand response programs, which use time and location shifting to balance electricity demand, can reduce energy costs and promote grid stability [7].
In conclusion, the transition to sustainable energy practices in data centers is not only environmentally responsible but also economically viable. As AI continues to drive innovation and growth, the sector must prioritize energy efficiency and renewable energy adoption to ensure a sustainable future. The call for 100% renewable energy by 2030 is a critical step towards achieving this goal.
References:
[1] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[2] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[3] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[4] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[5] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[6] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[7] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
MSFT--
UN Secretary-General Antonio Guterres urges the AI sector to prioritize sustainable energy for power-hungry data centers, which currently use the same amount of electricity as 100,000 regular homes. Guterres calls on major tech firms to power all data centers with 100% renewables by 2030 and notes that AI can boost efficiency and innovation in energy systems. Data centers currently account for 1.5% of global electricity consumption, set to more than double by 2030.
In a world increasingly reliant on artificial intelligence (AI), data centers have become the backbone of digital infrastructure. However, the energy demands of AI workloads pose significant challenges, with data centers consuming a substantial amount of electricity. According to the United Nations Secretary-General Antonio Guterres, the AI sector must prioritize sustainable energy practices to mitigate the environmental impact of these power-hungry facilities.Data centers currently account for 1.5% of global electricity consumption, a figure that is projected to more than double by 2030 [1]. This surge in energy demand is largely driven by the computational intensity of AI training and inference tasks. For instance, training large language models like GPT-4 requires over 65,000 megawatt-hours (MWh) of electricity, while AI searches consume nearly 10 times more energy than traditional searches [2].
To address this challenge, Guterres has called on major tech firms to power all data centers with 100% renewable energy by 2030. This ambitious goal aims to reduce the carbon footprint of data centers and promote sustainable energy practices. Several tech giants, including Google and Microsoft, have already made significant strides in this direction. Google has achieved 100% renewable energy and aims to produce 24/7 carbon-free energy by 2030 [3], while Microsoft has invested in alternative energy sources like hydrogen and nuclear reactors [4].
In addition to renewable energy adoption, data centers are exploring innovative solutions to enhance energy efficiency. Advanced cooling technologies, such as liquid cooling, offer significant potential to reduce energy consumption. A study found that fully implementing liquid cooling can reduce facility power consumption by 18.1% and total data center power by 10.2% compared to traditional air cooling [5]. Furthermore, data center infrastructure management (DCIM) software can optimize operations by monitoring power use and environmental conditions in real time.
The integration of AI in energy management is also gaining traction. AI-driven temperature regulation systems can predict temperature fluctuations based on equipment usage and weather conditions, conserving energy by adjusting cooling in real time [6]. Additionally, demand response programs, which use time and location shifting to balance electricity demand, can reduce energy costs and promote grid stability [7].
In conclusion, the transition to sustainable energy practices in data centers is not only environmentally responsible but also economically viable. As AI continues to drive innovation and growth, the sector must prioritize energy efficiency and renewable energy adoption to ensure a sustainable future. The call for 100% renewable energy by 2030 is a critical step towards achieving this goal.
References:
[1] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[2] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[3] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[4] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[5] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[6] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability
[7] https://www.wevolver.com/article/repowering-data-centers-for-ai-managing-energy-demand-and-sustainability

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