AI's Energy Appetite: US Data Centers Could Outconsume Germany and Japan's Combined Natural Gas Use

The AI boom isn't measured only in algorithmic performance or astronomical stock valuations — it's also measured in raw energy consumption. According to TechCrunch, US data centers could, by 2035, end up consuming more natural gas than Germany and Japan combined — two of the world's most energy-intensive industrial economies.

Where This Surge in Demand Is Coming From

Training and running large-scale AI models requires massive computing infrastructure that operates around the clock, regardless of fluctuations on the power grid. Big tech companies, under pressure to deliver ever more powerful capabilities in ever shorter timeframes, have started seeking energy sources that are both stable and quickly available. Natural gas has emerged as the preferred solution, particularly in areas where renewable grids cannot guarantee a constant supply.

In practice, digital infrastructure developers increasingly prefer to build dedicated gas-fired power plants or sign direct contracts with energy suppliers, sidestepping the bureaucratic and technical bottlenecks associated with connecting to the public electricity grid.

Economic and Environmental Implications

This trend raises an obvious dilemma for tech companies: public commitments to carbon neutrality now clash directly with the urgent need for reliable power. According to TechCrunch, the scenario under discussion would place US AI infrastructure among the world's largest industrial gas consumers — comparable to entire national economies.

For energy markets, such concentrated demand could push prices upward, affecting both household consumers and other industries that depend on natural gas. At the same time, investors in the energy sector see AI as a growth engine for gas infrastructure, at a moment when the shift toward renewable sources seemed to be diminishing the relevance of this fossil fuel.

What Comes Next for the Industry

For Romanian and European companies pursuing AI adoption, the situation in the US serves as a warning sign about the hidden costs of digital infrastructure. Business strategies that involve AI at scale must now treat the energy component as a factor of financial and reputational risk, not merely as a secondary technical detail.