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In just five years, AI could drive global electricity demand from data centres to more than double, rising from roughly 415 TWh in 2024 to about 945 TWh by 2030—an increase equivalent to adding another major economy’s power needs, such as today’s Japan, within a remarkably short span. The United States and China alone will account for nearly 80 percent of this surge, underscoring a widening gap in power demand between the two superpowers that risks deepening if AI-related onshoring accelerates. Meanwhile, critical constraints—metals, mining capacity, and grid infrastructure—are rapidly emerging as the linchpins for sustaining this digital-energy transformation.
AI’s Explosive Demand Growth
According to the IEA, global electricity consumption by data centres will more than double over the next five years, consuming as much power by 2030 as the whole of Japan uses today. This doubling is driven primarily by AI workloads, with dedicated AI data centres alone forecast to see their electricity demand quadruple by 2030. A recent study projects that top-tier AI supercomputers may require up to 9 GW—equivalent to nine nuclear reactors—by 2030, highlighting the scale of investment needed in generation capacity.
The U.S.–China Demand Disparity
In the IEA’s outlook, the United States will drive roughly half of global data centre power growth through 2030, while China follows closely as the second-largest contributor. Together, they will represent nearly 80 percent of the projected increase in data centre electricity consumption. By 2030, U.S. data centres are expected to consume more electricity for computing than for manufacturing all energy-intensive goods—aluminium, steel, cement, and chemicals—combined. In China, data centre consumption could reach between 400 TWh and 600 TWh by 2030, generating roughly 200 Mt CO₂e of emissions.
Onshoring and Infrastructure Imperative
If onshoring of AI capacity intensifies—driven by geopolitical realignment and supply-chain resilience—the United States could face a demand spike similar to China’s current trajectory. However, the IEA warns that up to 20 percent of planned data centre projects risk delays due to insufficient transmission infrastructure. U.S. utilities are already fielding unprecedented capacity requests, raising concerns about peak-demand shortages and grid stability. Accelerated grid upgrades, coupled with distributed energy resources and demand-response programs, will be essential to avoid bottlenecks.
Metals, Mining, and Materials Bottlenecks
According to the IEA, the surge in AI-driven power demand will strain critical-minerals supply chains. For example, gallium demand could exceed 10 percent of current global production by 2030, while other key materials—silicon, copper, and rare earth elements—face similar pressure. Expanding mining capacity and processing infrastructure will require significant capital and clear regulatory frameworks. Meanwhile, meeting both baseload and peak data centre loads will hinge on a diverse mix of natural gas, renewables, nuclear energy, and grid-scale storage.
Conclusion
AI’s meteoric rise is redefining electricity demand—and it isn’t a far-off scenario. It’s a power story unfolding now, with global data centre consumption set to swell by nearly 130 percent in five years. Stakeholders must unite around a comprehensive strategy—modernizing grids, securing critical-minerals supply chains, and diversifying generation portfolios—to ensure that this digital revolution doesn’t outpace our ability to power it. The time to act is today, before the charts overshoot our capacity to respond.