
Artificial intelligence (AI) is no longer just a buzzword - it’s now one of the world’s fastest-growing drivers of electricity demand. From powering large-scale language models to operating autonomous systems, AI is already reshaping the global energy map.
But all that progress comes with a cost:
AI Needs Power, A Lot Of Power
A new report from the International Energy Agency (IEA) highlights just how sharp the curve is. The IEA projects that global data center electricity consumption could reach 945 terawatt-hours (TWh) by 2030 - more than triple the 2020 level. That figure surpasses the current electricity consumption of the entire country of Japan.
AI-related workloads are set to quadruple, driven by compute-heavy applications in cloud computing, natural language processing, and image generation. These workloads require high-density power delivered consistently, something traditional sources struggle to guarantee at scale.
Enter Small Modular Reactors (SMRs), an emerging nuclear technology that offers low-emission, scalable, and always-on electricity, tailored for the exact kind of demand AI workloads require.
Some key advantages:
The IEA report notes that plans for up to 25 GW of SMR capacity have already been announced, much of it aimed at supporting data centers in the United States. The world stands at a unique crossroads: AI is accelerating at full speed, and energy systems must catch up. And as companies like Entra1 and NuScale work to bring these reactors online, a new energy narrative is emerging, one that matches the ambition of AI with the stability and sustainability of advanced nuclear power.
Read more from Wadie Habboush or download the IEA report "Energy and AI"
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