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    AI Powering Data Centres and Draining Energy

    AI's growing energy consumption in Asia is causing concerns about its environmental impact. This article explores potential solutions and upcoming regulations.

    Anonymous
    3 min read20 June 2024
    AI Energy Consumption in Asia

    AI Snapshot

    The TL;DR: what matters, fast.

    AI’s growing energy demands, particularly from data centers, are projected to more than double global electricity consumption by 2026, driven by energy-intensive AI model training.

    The rapid expansion of data centers in Asia, especially China, raises concerns about increased water consumption and threatens climate goals set by major tech companies.

    Potential solutions include more energy-efficient AI hardware and a shift to renewable energy sources, alongside increasing calls for regulation and transparency in the AI industry.

    Who should pay attention: Data centre operators | AI developers | Energy policymakers | Environmental regulators

    What changes next: Debate will intensify around AI energy consumption and sustainable data centre practices.

    AI's growing demand is causing a significant increase in data centre energy consumption, with predictions showing a more than double increase from 2022 to 2026.,The expansion of data centres in Asia, particularly in China, is raising concerns about energy usage and water consumption.,Efforts to mitigate environmental impact include advancements in chip hardware efficiency and exploring renewable energy sources.

    The AI Energy Conundrum

    Artificial Intelligence (AI) is transforming the world in ways we never imagined. However, this transformation comes with a hefty price tag: a colossal consumption of energy. Power-hungry data centres across the globe are working round the clock to support AI's insatiable appetite for energy. The International Energy Agency (IEA) forecasts that global data centre electricity demand will more than double from 2022 to 2026, with AI playing a significant role in this surge.

    Data Centres: The Backbone of AI

    Data centres are massive facilities filled with thousands of computer servers running continuously. In the era of 5G and cloud-based storage, they have become indispensable, supporting everything from financial transactions to social media and government operations. They require a constant and reliable energy supply, accounting for more than 1% of global electricity use.

    AI's rapid growth has dramatically accelerated data centre construction and usage. Training AI models is extremely energy-intensive, consuming power at a much higher rate than traditional data centre activities. For instance, a ChatGPT query uses ten times more energy than a standard Google query. For more on how people are using this technology, see How People Really Use AI in 2025.

    AI vs. Climate Goals: The Asian Perspective

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    This energy usage surge threatens to undermine climate pledges made by major tech companies. In Asia, data centres are growing rapidly, particularly in China. The Hong Kong-based think tank China Water Risk estimates that data centres in China consume 1.3 billion cubic meters of water per year, nearly double the volume used by the city of Tianjin for households and services. This growth is part of a broader trend of AI Boom Fuels Asian Market Surge.

    Potential Solutions

    AI companies are working on solutions to reduce energy consumption. Efficiency improvements in chip hardware, such as NVIDIA's new line of GPUs with 25 times lower energy consumption, could significantly reduce energy usage. Additionally, AI technology could help combat climate change by addressing inefficiencies. This push for efficiency is also seen in other areas, such as Nvidia Jetson AGX Thor sets a new pace for robotics and physical AI.

    Industry leaders are also investing in renewable energy sources like wind, solar, and nuclear power. However, many data centres still rely on fossil fuels, especially during the transition period.

    Regulation on the Horizon

    Regulation may be imminent. The European Commission is moving towards regulating data centre sustainability across the EU. In the US, the House Committee on Energy and Commerce held a hearing about AI's energy usage in June. Transparency is key to understanding AI's environmental impact and implementing effective regulations. This is a global concern, as countries like Taiwan’s AI Law Is Quietly Redefining What “Responsible Innovation” Means. For more detailed information on data center energy consumption and its environmental impact, the International Energy Agency provides comprehensive reports here.

    Comment and Share:

    What are your thoughts on AI's growing energy consumption? Do you believe that advancements in hardware efficiency and renewable energy sources can mitigate its environmental impact? Share your thoughts below and don't forget to Subscribe to our newsletter for updates on AI and AGI developments at AI in Asia.

    Anonymous
    3 min read20 June 2024

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    Latest Comments (3)

    Manuel Gonzales
    Manuel Gonzales@manny_g_dev
    AI
    10 December 2025

    Aye, this energy drain is a real bother here in the Philippines too. Our grids are already stressed, what more with these power-hungry AI centers?

    Monica Teo
    Monica Teo@monicateo
    AI
    15 August 2024

    I wonder if we're barking up the wrong tree focusing solely on the data centres. What about the energy used to *produce* all those AI models and the devices running them? The entire lifecycle is surely a bigger piece of the puzzle. Maybe a holistic sustainability approach is what's truly needed, rather than just zooming in on one aspect.

    Henry Chua
    Henry Chua@hchua_tech
    AI
    25 July 2024

    Wah, this is really timely, I was just reading something similar. It’s crazy how much juice these AI servers are using, you know? I live in a HDB flat and sometimes the heat in my area is already mad, I can’t imagine what powering these mega datacentres is doing to the grid and the environment. Definitely worth keeping an eye on.

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