“China is going to win the artificial intelligence race,” warned Jensen Huang, CEO of Nvidia. Many thought he was exaggerating, interested in fueling demand for his chips. But, as analyst June Yoon explained in her column for the Financial TimesHuang’s argument contains an uncomfortable truth: the availability of electricity—not chips—is becoming the critical factor for the development of AI.
A model like GPT-4 can consume more than 460,000 megawatt-hours per year, the equivalent of the energy consumption of 35,000 American homes, according to a study. The world’s data centers—already colossal—could double their electricity consumption before 2030. And that changes the rules of the game.
When there are plenty of chips, but there are no plugs. The race for AI It started with a GPU fever. Big tech companies rushed to buy every Nvidia chip available, but they soon discovered something more worrying: there weren’t enough sockets to connect them. Satya Nadella himself, CEO of Microsoft, he said it bluntly: “The biggest problem we have now is not excess chips, but energy.”
Electricity demand has skyrocketed so much that Google, Microsoft and Amazon are already contemplating build nuclear reactors to keep your servers on. The paradox sums up the moment well: the digital leadership of the West encounters a physical limit, that of cheap energy.
Energy as a new geopolitics. Analyst June Yoon throw a question that reorders the technological map: what if the AI race had nothing to do with chips, but with electricity? If the last century was defined by oil, this one will be defined by the current
China no longer lives off oil: generates it. It has gone from being a petrostate dependent on crude oil to becoming the first electrostate on the planet. More than one quarter of your electricity It comes from renewable sources and its network is growing at a speed that no other country can match. Now that energy sovereignty fuels a new front: artificial intelligence.
How did you find the formula? Since September, the Chinese Government Subsidizes up to 50% of energy costs of data centers that use national chips. The inland provinces—Guizhou, Gansu, Inner Mongolia—have become “electric hearts” of Chinese AI: there energy is abundant and cheapand local governments offer historically low rates of just 0.4 yuan per kilowatt-hour.
The measure has a dual purpose:
- Compensate for the lower efficiency of domestic chips compared to Nvidia’s.
- Promote technological independence in the midst of a trade war.
As Bloomberg has detailedthese regions are connected by ultra-high voltage (UHV) lines that transport renewable energy from the interior to the coastal areas where big technology companies, such as Alibaba, Tencent and ByteDance, are concentrated. The goal is clear: ensure abundant, low-cost energy for AI training clusters. According to Rystad Energythe electricity consumption of data centers could more than double before 2030, reaching 1,800 terawatt-hours in 2040. Beijing is preparing to absorb it.
The result is a planned, centralized energy ecosystem designed to scale AI. An example is the Talatan Solar Parkwhich extends like a sea of metal mirrors: more than 600 square kilometers of panels that are combined with wind and hydroelectric parks. From there, the power travels along high-voltage lines to data centers on the coast. It is a postcard of the new Chinese power: sun, wind and silicon.
China’s electrical advantage. The strategy is also working in the markets. According to Bloombergshares of Chinese power companies have risen up to 40% in a week, driven by demand for AI data centers. UBS forecasts that electricity demand in China will grow 8% annually until 2028.
Meanwhile, in Washington, the Trump administration has launched an AI Action Plan to accelerate the construction of data centers and remove obstacles to energy projects. But, as FT analysts point outchip improvements are stuck in single digits, while Chinese renewable energy grows by double digits every year.
The power is in the socket. In the race for artificial intelligence, chips are the brain. But the heart beats with electricity. The United States retains leadership and has the best semiconductors (for now); China, the network that keeps them on.
As June Yoon wroteall the technological superpowers in history—from coal England to oil America—were built on a source of cheap energy. Today, artificial intelligence needs electricity as it once needed steam. And on that new board, China seems to have found the key: plug in the future before anyone else.
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