China is now offering deep electricity discounts to data centers that use domestically made AI chips, aiming to accelerate the country’s shift away from foreign hardware. Provinces such as Gansu and Guizhou are lowering power costs by as much as half, making it financially attractive for major tech firms to train and deploy AI models with local silicon. The plan links national industrial ambition with practical cost relief.
The timing is not accidental. Chinese AI chips still trail behind leading global models in efficiency and performance. Training large models on local chips consumes more energy, which can drive costs sharply upward. By reducing the price of electricity, authorities compensate for this weakness, helping companies keep AI development affordable while giving domestic chipmakers room to mature.
This subsidy strategy also reflects broader geopolitical pressure. Export controls have restricted access to cutting-edge foreign chips, forcing China to accelerate self-reliance in semiconductor and data infrastructure. Rather than attempting to immediately match global chip performance, China is using policy levers to build an ecosystem first, betting that scale and local innovation will gradually narrow the gap.
The approach also signals a new competitive dimension in global AI: energy economics. Where hardware advantage is limited, lowering power cost becomes the lever. As data centers expand and AI computation demands continue to rise, the price of electricity could become just as influential as chip architecture in shaping who leads the next wave of computing.
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