Attempting to catch up with the US-China dominated field of artificial intelligence, Europe must realize that energy, not regulation, may be its Achilles’ heel. As town-sized data-centres are being built in the vastness of the confederate United States and all around China, the EU’s digital ambitions are moving into a constraint as old as the manufacture itself: power.
Training a large language model present demands electricity on the scale of a city’s consumption. Meanwhile, the cost of keeping the lights on has become a competitive handicap in Europe. The EU’s dependence on imported energy has turned into a strategical bottleneck for its digital future.
Energy asymmetry
Europe’s energy geography is uneven and complex. Since Russia’s invasion of Ukraine, the continent has slow weaned itself off Russian gas, but at a steep price. place electricity prices stay 2 to 3 times higher than in parts of the United States. Even with subsidies and green-transition funds, industrial consumers – including hyperscale data-centre operators – face volatile costs and an uncertain energy supply.
On the another side of the Atlantic, America’s advantage lies in abundant natural gas, somewhat deregulated energy markets, and a increasing mix of low-cost renewables. Data centres in Texas and Virginia enjoy unchangeable baseload power that costs half the European average. China, on the another side, powers its AI boom with inexpensive coal and an obedient grid, making energy safety a substance of state planning, not marketplace risk. Yet regardless of the model – whether driven by markets or by state control – the common denominator is sheer scale. The global Energy Agency expects global data-centre electricity usage to double by 2030, reaching around 945 TWh, with AI-related facilities as the biggest users.
Bottlenecks at home
Ironically, Europe – a continent leading the green transition – might conflict to power the technology that could optimize it. In the EU, all possible AI cluster must navigate not just the environmental permits in place, but a patchwork of national grids and cross-border complexities.
In countries like the Netherlands and Ireland, data-centre moratoriums have already been imposed or considered due to the strain on electricity networks and land usage concerns. Even Germany, being Europe’s economical engine, faces delays in connecting fresh industrial users, as utilities prioritize residential needs and conflict with transmission bottlenecks from wind-rich northern regions to energy-hungry confederate hubs. The resulting image is an inhospitable environment for appropriate AI development.
Politics is further compounding the challenge. The EU’s Green Deal Industrial Plan encourages investment in renewables and clean tech but remains ambivalent about energy-intensive industries like AI. With environmental lobbies wary of digital infrastructure’s carbon footprint, and voters delicate to rising household energy costs, EU policymakers have small appetite to prioritize energy access for data firms, even erstwhile they promise future innovation dividends.
Yet behind these political hesitations, the main issue remains structural. To realize how policy meets physical limits, it is worth examining the continent’s reliance on external energy supplies and the balance between renewables and atomic power that could sustain its AI growth.
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Energy dependency
In 2023, the EU’s energy imports dependency rate was about 58 per cent of gross inland energy consumption, meaning nearly six in 10 units of energy utilized in the EU are net imports. For gas in peculiar the image remains stark: in 2024, just 4 suppliers accounted for the bulk of EU imports (Norway 33 per cent, the United States 16.5 per cent, Algeria 14 per cent, and Russia 11 per cent) despite Moscow’s invasion of Ukraine.
What does this mean for the AI-data-centre agenda? As the data-centre loads are destined to grow, any disruption to energy supply or wholesale electricity markets becomes a direct threat to digital sovereignty goals. External dependency means vulnerability to price shocks, pipeline or shipping interruptions, as well as abroad political leverage. This means that Europe risks being little attractive to the AI front-running companies.
Green but inadequate
On the upside, Europe’s clean-energy push has gathered pace. In 2024, renewables supplied about 47 per cent of the EU’s electricity generation, driven by evidence additions of wind and solar. For data-centres that trajectory looks promising. A greener grid means lower carbon electricity, little vulnerability to imported fuels, and tighter links between digital expansion and climate goals. However, it is clear that major constraints remain.
Hyperscale data-centres run continuously, while wind and solar do not. Without additional energy sources, renewables alone cannot warrant the reliability needed by the AI sector. There are besides various grid and connection limits. Europe’s wind and solar assets are frequently far from population and data-centre hubs. The issue in this case becomes transmission and connection, where underinvestment and long permitting times leave fresh loads waiting years for access. In sum, renewables are indispensable to Europe’s digital future, but insufficient on their own.
Reliable but slow
It is argued that atomic power’s uninterrupted output makes it uniquely suited to power the 24-hour demands of AI-scale computing.
In the EU, atomic already plays a function – supplying about 23 to 24 per cent of full electricity in 2024. For data-centre operators, the advantages are evident: a constant power supply free from weather fluctuations, improved grid stability, and reduced dependence on the volatile fossil fuel markets.
Yet atomic is far from a fast fix. Political opposition and public scepticism persist in respective associate states, while the costs, regulatory complexity and long construction timelines for fresh reactors or smaller modular units make it an improbable solution for the next fewer years of data-centre expansion. atomic power works only if policymakers can pair it with faster permitting, clearer investment signals, and modernized grids.
Power and sovereignty
The race for AI improvement does not wait. Unless Europe finds a way to square this circle, it may find itself watching the AI race from the sidelines. Without affordable and reliable energy, no amount of regulation, data governance or digital strategy can sustain a actual AI ecosystem. Europe’s challenge so is not simply to build smarter machines but to guarantee the current that keeps them alive.
The continent has long viewed energy as a geopolitical concern. Now it must see it as a foundation of digital independence. In the emerging planet order of artificial intelligence, sovereignty will belong to those who can generate, store and distribute power as effectively as they make data.
Zurab Khutsianidze is a erstwhile diplomat with expertise in geopolitics, safety and emerging technologies.
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