EU’s $20bn AI Gigafactory Plan: A Bold Gamble to Catch Up in the Global AI Race

For years, the European Union has lagged far behind in the artificial intelligence race, watching from the sidelines as the United States and China pulled ahead with aggressive investments in computing infrastructure, AI models, and semiconductor technology.

While Silicon Valley tech giants like OpenAI, Google DeepMind, and Meta dominate AI research and commercial applications, China has built state-backed AI powerhouses that have fueled breakthroughs in machine learning and deep learning.

By comparison, Europe has struggled to establish itself as a major player in AI development, weighed down by bureaucratic inefficiencies, fragmented policies across member states, and a lack of homegrown tech giants capable of competing on a global scale. The bloc has historically been more focused on regulating the tech sector than fostering innovation, creating an environment where companies often face stringent compliance requirements rather than encouragement to experiment and expand.

Now, in an effort to reverse its dwindling influence in AI, the European Commission has unveiled a $20 billion plan to construct four “AI gigafactories”—large-scale public-access data centers designed to provide the computing power needed to train advanced AI models. European Commission President Ursula von der Leyen described the initiative, which has been compared to the U.S.’ Stargate, as a public-private partnership aimed at ensuring that Europe can develop the large-scale AI models necessary to become an AI powerhouse.

The gigafactory initiative is part of InvestAI, the EU’s €200 billion ($216.92 billion) strategy to close the AI gap with the United States and China. However, many industry experts remain skeptical about its feasibility. They warn that significant obstacles—including chip shortages, energy constraints, and the bloc’s heavy-handed regulatory approach—could ultimately hinder its success.

Unlike the United States, where AI development is largely driven by private-sector innovation and backed by massive capital investments from tech companies and venture capitalists, Europe’s AI strategy has been slower and more state-driven. This has been attributed to the EU’s long-prioritized tight regulation of the tech sector, which places a stronger emphasis on data privacy, ethics, and competition laws than on fueling rapid technological growth.

This regulatory-first approach has resulted in accusations that the bloc is stifling innovation, making it harder for European AI startups to compete with their American and Chinese counterparts. While the United States has adopted a laissez-faire approach, allowing companies like OpenAI, Microsoft, and Google to scale their AI operations with minimal government interference, Europe has spent years debating and drafting laws to regulate AI and Big Tech companies.

The bloc’s AI Act, expected to be the world’s first comprehensive AI law, is set to impose strict rules on AI development, banning certain high-risk AI applications and requiring companies to disclose how their AI models function. Many believe that these regulations, while well-intentioned, slow down European AI research and make it even less attractive for investment compared to the U.S. and China. Analysts believe that AI will not be spared from the EU’s restrictive regulatory approach, which has already impacted the growth of tech giants in the region.

Can the Gigafactory Change the Narrative?

With the AI gigafactory plan, the EU hopes to establish its own AI infrastructure, allowing European companies, researchers, and startups to train their own AI models without having to rely on U.S. or Chinese cloud providers like Amazon Web Services (AWS), Microsoft Azure, or Alibaba Cloud. However, some experts question whether Europe has the right ecosystem to make use of these facilities, arguing that building AI hardware alone is not enough to close the gap with the United States and China.

Bertin Martens, an economist at the Brussels-based think tank Bruegel, questioned the logic of the investment, arguing that it is unclear how the EU will effectively use these gigafactories once they are built.

“Even if we would build such a big computing factory in Europe, and even if we would train a model on that infrastructure, once it’s ready, what do we do with it?” Martens asked.

The gigafactories are expected to contain 100,000 cutting-edge AI chips each, making them four times larger than the Jupiter supercomputer, currently under construction in Germany. However, this still pales in comparison to AI projects in the U.S. Meta, for example, is building a 1.3 million GPU facility in Louisiana, powered by 1.5 gigawatts of electricity, dwarfing Europe’s planned investments in AI computing.

Challenges: Chip Shortages, Energy Constraints, and U.S. Export Restrictions

Beyond regulatory concerns, the EU also faces major logistical challenges in building these gigafactories.

Reuters reported that one of the biggest hurdles is securing enough high-performance AI chips, particularly Nvidia’s H100 GPUs, which are critical for training AI models. These chips are in short supply worldwide, and their price—currently around $40,000 each—makes mass procurement a daunting task.

To complicate matters, the United States has imposed export controls on advanced AI chips, restricting sales to China and certain European countries to prevent foreign AI competitors from gaining access to cutting-edge technology. While it remains uncertain whether the next U.S. administration will tighten or loosen these restrictions, current policies could make it harder for the EU to acquire the chips needed to build and operate its gigafactories.

Energy supply is another major concern. AI supercomputers consume massive amounts of electricity, and Europe—already struggling with high energy costs and power shortages—may face difficulties finding the infrastructure to support these massive AI factories.

Kevin Restivo, a data center expert at CBRE, warned that the gigafactories will face the same challenges as private AI data centers in Europe, including difficulty obtaining chips and securing enough electricity to power large-scale AI training.

“There’s nothing to say that the government can’t get its hands on those chips or that great projects can’t come from it, but it’s unlikely to happen in the short term,” Restivo said.

Can Europe Overcome Its AI Weaknesses?

The EU now seems committed to expanding its AI capabilities. In addition to the gigafactory plan, the European Commission is upgrading 12 scientific supercomputing centers to turn them into AI hubs. These supercomputers are already being used for AI and machine learning research, and their expansion could help drive AI innovation across Europe.

However, Europe’s previous attempts to establish itself as a technology leader have produced mixed results. The 2023 EU Chips Act, which aimed to increase Europe’s share of global semiconductor production to 20%, failed to meet its goals, leading instead to investments in specialized chips for the automotive sector rather than cutting-edge AI hardware.

Many fear that the AI gigafactory initiative could suffer a similar fate, with billions spent on infrastructure that fails to create a self-sustaining AI ecosystem.

For some, however, the initiative presents an opportunity for European AI startups and local semiconductor firms. Companies like France’s SiPearl and the Netherlands’ AxeleraAI, which develop AI chips, could benefit from increased funding and infrastructure for AI research.

Kimmo Koski, managing director of Finland’s LUMI supercomputer, believes that AI gigafactories could help drive industrial AI applications, which would be a major step forward for Europe.

“In my understanding, it relates to pushing industry use further,” Koski said. “That would be an innovation in Europe, a very welcome event of course.”

Only time will tell whether these investments will be enough to help Europe compete with the United States and China. However, one thing is clear: Europe is finally waking up to the AI race—for the first time, making a statement that is drawing attention.