European Gigafactories: 5 Sites to Make Up 15 Years of Technological Lag

Europe is preparing to deploy considerable investments to build artificial intelligence gigafactories. Facing it, American giants have invested massive sums, creating an asymmetry that reveals the scale of Europe’s challenge: catching up on an abyssal technological lag while preserving digital sovereignty that remains largely theoretical.

This critical infrastructure raises major questions: energy dependency, indispensable American technologies, and Asian production capabilities. Europe is betting heavily on an industrial strategy that could redefine its place in the AI race — or confirm its status as a second-rank power.

But executing this ambitious plan already faces major obstacles that question its very feasibility. The European Union’s plan to mobilize 20 billion euros for a network of AI “gigafactories” is hitting delays and funding uncertainty, fueling concerns about Europe’s ability to compete in the global race for AI infrastructure.

The Essentials

  • Europe is investing billions of euros in AI gigafactories against massive investments by American companies
  • Lack of funding clarity means that only two of the five planned centers can receive money before the next EU budget cycle begins in 2028
  • These facilities will concentrate a significant number of high-performance computing chips
  • Energy needs will be considerable, representing consumption equivalent to that of a small European country
  • A significant share of critical components will remain imported from Asia despite European investments
  • The initiative, initially announced last year, first attracted interest from approximately 70 companies across the bloc. This number has shrunk to about 10 groups expected to submit bids

Five Sites to Reverse Fifteen Years of Technological Lag

European gigafactories will be located in Germany, France, Italy, Spain and the Netherlands by 2027. Each site will concentrate more than 100,000 advanced AI processors in buildings of several tens of thousands of square meters, cooled by pressurized liquid systems. Combined computing power will reach considerable capacities.

This infrastructure aims to fill a glaring deficit. According to the Stanford AI Index 2025, Europe currently has only 3% of global AI computing capacity, compared to 54% for the United States and 28% for China. European companies are heavily dependent on American cloud services: AWS, Microsoft Azure and Google Cloud monopolize a major share of Europe’s AI market.

The plan provides for the creation of a substantial number of direct jobs, mainly engineers specialized in systems architecture and industrial cooling. But Europe will have to import almost all the talent: European universities train fewer AI PhDs than their American and Chinese counterparts.

However, the request for proposals process, originally scheduled for May, has been postponed to July. At least two consortiums are reconsidering whether they should bid at all if the project is significantly reduced, according to people familiar with the matter. This hesitation reflects the uncertainty hanging over the entire project.

The golden age of industry to come may well be decided by this capacity to attract the best minds to these new technological temples.

The Energy Bill That Makes the Electric Grid Tremble

Each gigafactory will consume several hundred megawatts continuously, equivalent to a medium-sized city. The cumulative consumption of the five sites will reach several terawatt-hours per year, exceeding the annual electricity demand of some European countries. This explosion in needs comes as Europe is already struggling to secure its energy supply.

Germany will host one of the largest gigafactories near Cologne, but will have to import French electricity to power its chips. France will install its site in Normandy, benefiting from proximity to nuclear reactors, but questioning the capacity of the regional grid. Italy is betting on Sicilian solar energy with giant storage batteries.

According to Goldman Sachs Research, global electricity demand for data centers will increase by 50% by 2027 and by 165% by the end of the decade, compared to 2023. In France, a new report by Ademe estimates that electricity consumption by data centers could be multiplied by 3.7 by 2035 (37 TWh).

Energy costs will represent a significant portion of operating expenses, several billion euros annually for the five sites. By comparison, Google’s data centers already consume massive amounts of energy worldwide, but benefit from privileged energy agreements negotiated over long periods.

This energy dependency exposes Europe to a strategic vulnerability: any electricity crisis could instantly paralyze its AI computing capacity. American giants diversify their supplies across multiple states and invest heavily in their own solar plants.

But uncertainty extends beyond energy supply alone. The phased funding structure, with money scheduled for 2028 and 2030, means subsidies arrive years after the infrastructure is needed. This temporal mismatch complicates planning for private investors who must advance funds long before receiving public subsidies.

Technological Dependency Persists Despite Investments

A major paradox of the European plan: a significant portion of critical components will continue to be imported. Nvidia H100 chips will equip the German and French gigafactories, AMD MI300X will power the Italian and Spanish sites, while the Netherlands will test the new Intel Gaudi 3 chips. No European alternative exists.

TSMC, the Taiwanese manufacturer, will produce all processors. Samsung will supply high-bandwidth memory. Cooling systems will come from Japanese company Nidec. Only buildings and electrical systems will be European, representing a fraction of total added value.

This dependency extends to software: Nvidia’s CUDA remains essential for a large majority of machine learning applications. European alternatives like British Graphcore chips achieve only a fraction of the performance of American benchmarks on language models.

Europe is trying to compensate through research: the Horizon Europe program will allocate billions of euros over several years to developing sovereign processors. But the first European prototypes won’t arrive before 2030, several technological generations behind.

Worse still, the EU’s AI gigafactories risk not achieving the Commission’s ambitions, as several unresolved challenges threaten their success. For example, by the time the first gigafactories enter service in 2027-2028, the largest foreign data centers will already have a considerable technological lead.

AI increases wages without destroying jobs, for now, but this positive dynamic depends entirely on access to cutting-edge technologies that Europe does not yet control.

Considerable but Asymmetric Investments Against American Giants

The European effort, while significant, remains limited against American investments. Meta has spent tens of billions of dollars on its AI infrastructure. Microsoft has invested massively, as have Google and Amazon. Nvidia has generated considerable revenue selling its chips, primarily to these same giants.

American public utilities alone plan to spend 1.4 trillion dollars on network infrastructure for AI by 2030, and American hyperscalers invest hundreds of billions annually in data centers, including on European soil. SoftBank recently announced up to 75 billion euros of investment in data centers in France alone, more than three times the entire EU program. Meta is raising 13 billion dollars for a single data center in Texas.

This financial asymmetry translates into a gaping technological gap. OpenAI’s GPT-4 required thousands of A100 chips for its training. Future models will likely mobilize hundreds of thousands of chips, potentially exceeding the combined capacity of European sites.

American giants are already developing their successors: Google is testing more powerful TPU chips, Microsoft is designing Maia processors optimized for its models, Meta is finalizing its next-generation MTIA chips. Europe is investing in today’s technology while the United States is building tomorrow’s.

The problem is worsening with European funding uncertainty. The 20-billion-euro plan calls for less than half coming from governments. The EU would provide 4.1 billion euros in subsidies, matched by an equivalent amount from member states hosting the centers, with private investors funding the rest. But this complex structure discourages investors facing market urgency.

Worse still: European companies will continue paying an “AI tax” to American platforms. According to Eurostat, EU companies have paid billions of euros for AI services hosted across the Atlantic. European gigafactories will allow them to repatriate some of this value, but not reverse it.

European Expertise Seeks Its Path Between Research and Industrialization

Europe is betting on its distinctive assets to capitalize on its gigafactories. CERN is developing revolutionary optimization algorithms for particle physics. French INRIA excels in symbolic AI and robotics. The German Max Planck Institute is innovating in federated learning, this technique that preserves data privacy.

These laboratories will feed the gigafactories with specialized use cases where Europe can still compete: climate simulation, drug discovery, industrial optimization. Airbus will use a gigafactory to design its future aircraft through generative AI. ASML will exploit a site to improve its chip engraving machines.

But the European ecosystem struggles to transform academic excellence into commercial success. Europe has fewer technological “unicorns” than the United States and China. European talent is migrating massively to Silicon Valley: a significant share of European AI researchers now work for American companies.

Gigafactories could reverse this brain drain by offering research infrastructure comparable to those of Google or Microsoft. But they must first convince European researchers to return home with competitive salaries and ambitious projects.

Uncertainty about construction schedules further complicates talent attraction. The European Commission has postponed several times the publication of its criteria for data centers. Without clear visibility on technical specifications and deadlines, the best AI engineers prefer to join American or Chinese projects already operational.

The Bet on Specialization Against Generalist Hegemony

Unable to compete on volume, Europe chooses specialization. Each gigafactory will focus on specific domains: healthcare in France, automotive in Germany, energy in the Netherlands, aerospace in Spain, finance in Italy. This vertical approach contrasts with the American horizontal strategy where the same infrastructure serves all sectors.

The European healthcare sector could gain an advantage. Strict GDPR regulations constrain American giants, creating a competitive advantage for local companies. A gigafactory will develop AI medical models that respect privacy, an asset against less scrupulous American solutions.

Same logic in automotive: European manufacturers refuse to share their data with American platforms. BMW, Volkswagen and Stellantis prefer to develop their AI on European soil. A gigafactory will meet this demand with models specialized in autonomous driving adapted to European roads.

This niche strategy presents a major risk: fragmentation. The five gigafactories could develop incompatible ecosystems, reducing economies of scale and complicating the emergence of global European champions. The United States dominates precisely because it pools its investments on universal platforms.

But specialization may never materialize if delays accumulate. A lack of clarity on demand and when subsidies will be available threatens to undermine the initiative, according to people familiar with the matter. European companies risk turning to American solutions rather than waiting for hypothetical infrastructure.

Europe has a few years to demonstrate that its gigafactories can create a credible alternative to American solutions. Five sites, considerable investments, colossal energy challenges and persistent technological dependency: Europe’s AI bet is just beginning, but it will determine the continent’s place in the digital economy of the coming decades.

Between technological sovereignty and economic realism, Europe is still seeking its path in a world where artificial intelligence is reshaping power dynamics. The obstacles emerging in the project’s preliminary phases illustrate the scale of the challenge: making up fifteen years of technological lag with limited means, hesitant partners and receding deadlines. Success is no longer guaranteed; it becomes uncertain.