As AI Companies Race for Power, Amazon and Google Have the Lead by Jinjoo Lee
Amazon has an incumbent advantage, and Google stands out for some innovative approaches. The rapid adoption of AI has intensified power demand among hyperscale cloud companies, with Amazon and Google at the forefront. Amazon’s US self-built data centers now use up to 9 gigawatts of power, a figure comparable to an entire state’s generation capacity. Google and Microsoft trail with capacities around 5 gigawatts each, while Meta sits at 4 gigawatts. The competition is not merely about expansion but also about securing reliable, scalable power sources to meet the growing requirements of AI workloads. All the hyperscalers have also placed bets on novel technology providers that promise to eventually supply cheap, clean, reliable and fast energy. These range from small modular nuclear reactors, advanced geothermal and novel batteries to solar energy beamed in from space. SpaceX and Google are even eyeing data centers in space. As AI Companies Race for Power, Amazon and Google Have the Lead – WSJ


The rapid advancement of artificial intelligence (AI)—particularly the training of large-scale “frontier models”—is driving renewed growth in electricity demand. This report analyzes the technical drivers of AI power consumption, projects future demand trajectories for individual training sites and broader AI needs, and highlights energy sector implications. Their analysis found not only that the power demands of AI have increased steadily, but also that they will keep increasing. While training large, advanced AI models currently requires between 100 and 150 megawatts each, they are projected to require more than four gigawatts apiece by 2030.This Product is publicly available at Electric Power Research Institute (EPRI): 