"World of DaaS" The LM Brief: The Energy Bottleneck Behind AI’s Growth
Oct 17, 2025
Electricity is fast becoming the ultimate bottleneck for AI development. As demand for data centers skyrockets, reliable power is now the competitive edge. Countries are looking into nuclear-powered facilities to secure energy supply. The predicted energy consumption of global data centers by 2030 is staggering, with the U.S. set to account for a significant share. Modern AI racks require immense power, and cooling demands further complicate efficiency. Innovations in power supply and infrastructure are crucial for sustaining AI's rapid growth.
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AI Energy Demand Could Rival Nations
- Data center electricity use was about 415 TWh in 2024 and could nearly double to ~945 TWh by 2030.
- That growth would make global data center demand comparable to the annual electricity of a large industrialized country.
U.S. Faces Massive Grid Demands
- The U.S. may account for nearly half of global growth in data center electricity demand.
- U.S. data center consumption could approach 800 TWh, requiring over 80 GW of extra capacity by 2030.
Computation, Cooling, And Sustained Loads
- AI workloads draw power from computation, cooling, and sustained operation patterns.
- Training and inference run near-constantly, turning small per-prompt energy into massive aggregate consumption.