Data storage tapes are stored at the National Energy Research Scientific Computing Center (NERSC) facility at the Lawrence Berkeley National Laboratory, which will house the U.S. supercomputer to be powered by Nvidia’s forthcoming Vera Rubin chips, in Berkeley, California, U.S. May 29, 2025.
Manuel Orbegozo | Reuters
Europe is setting its sights on gigawatt factories in a bid to bolster its lagging artificial intelligence industry and meet the challenges of a rapidly-changing sector.
Buzz around the concept of factories that industrialize manufacturing AI has gained ground in recent months, particularly as Nvidia CEO Jensen Huang stressed the importance of the infrastructure at a June event. Huang hailed a new “industrial revolution” at the GTC conference in Paris, France, and said his firm was working to help countries build revenue-generating AI factories through partnerships in France, Italy and the U.K.
For its part, the European Union describes the factories as a “dynamic ecosystem” that brings together computing power, data and talent to create AI models and applications.
The bloc has long been a laggard behind the U.S. and China in the race to scale up artificial intelligence. With 27 members in the union, the region is slower to act when it comes to agreeing new legislation. Higher energy costs, permitting delays and a grid in dire need of modernization can also hamper developments.
Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, told CNBC that the bloc’s goal is to bring together high quality data sets, computing capacity and researchers, all in one place.
“We have, for example, 30% more researchers per capita than the U.S. has, focused on AI. Also we have around 7,000 startups [that] are developing AI, but the main obstacle for them is that they have very limited computing capacity. And that’s why we decided that, together with our member states, we are investing in this very crucial infrastructure,” she said.
These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories.
Henna Virkkunen
European Commission’s executive vice president for tech sovereignty
“We have everything what is needed to be competitive in this sector, but at the same time we want to build up our technological sovereignty and our competitiveness.”
So far, the EU has put up 10 billion euros ($11.8 billion) in funding to set up 13 AI factories and 20 billion euros as a starting point for investment in the gigafactories, marking what it says is the “largest public investment in AI in the world.” The bloc has already received 76 expressions of interest in the gigafactories from 16 member states across 60 sites, Virkkunen said.
The call for interest in gigafactories was “overwhelming,” going far beyond the bloc’s expectations, Virkkunen noted. However, in order for the factories to make a noteworthy addition to Europe’s computing capacity, significantly more investment will be required from the private sector to fund the expensive infrastructure.
‘Intelligence revolution’
The EU describes the facilities as a “one-stop shop” for AI firms. They’re intended to mirror the process carried out in industrial factories, which transform raw materials into goods and services. With an AI factory, raw data goes into the input, and advanced AI products are the expected outcome.
It’s essentially a data center with additional infrastructure related to how the technology will be adopted, according to Andre Kukhnin, equity research analyst at UBS.
“The idea is to create GPU [graphics processing units] capacity, so to basically build data centers with GPUs that can train models and run inference… and then to create an infrastructure that allows you to make this accessible to SMEs and parties that would not be able to just go and build their own,” Kukhnin said.
How the facility will be used is key to its designation as an AI factory, adds Martin Wilkie, research analyst at Citi.
“You’re creating a platform by having these chips that have insane levels of compute capacity,” he said. “And if you’ve attached it to a grid that is able to get the power to actually use them to full capacity, then the world is at your feet. You have this enormous ability to do something, but what the success of it is, will be defined by what you use it for.”
Telecommunications firm Telenor is already exploring possible use cases for such facilities with the launch of its AI factory in Norway in November last year. The company currently has a small cluster of GPUs up and running, as it looks to test the market before scaling up.
Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen and EVP Infrastructure Jannicke Hilland in front of a Nvidia rack at the firm’s AI factory
Telenor
“The journey started with a belief — Nvidia had a belief that every country needs to produce its own intelligence,” Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen told CNBC.
Hilsen stressed that data sovereignty is key. “If you want to use AI to innovate and to make business more efficient, then you’re potentially putting business critical and business sensitive information into these AI models,” she said.
The company is working with BabelSpeak, which Hilsen described as a Norwegian version of ChatGPT. The technology translates sensitive dialogues, such as its pilot with the border police who can’t use public translation services because of security issues.
We’re experiencing an “intelligence revolution” whereby “sovereign AI factories can really help advance society,” Hilsen said.
Billion-euro investments
Virkkunen said the region’s first AI factory will be operational in coming weeks, with one of the biggest projects launching in Munich, Germany in the first days of September. It’s a different story for the gigafactories.
“These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories, and it means billions in investments. Each of these need three to five billion [euros] in investment,” the commissioner said, adding that the bloc will look to set up a consortium of partners and then officially open a call for investment later this year.
Bertin Martens, senior research fellow at Bruegel, questioned why such investments needed to subsidized by government funds.
“We don’t know yet how much private investment has been proposed as a complement to the taxpayer subsidy, and what capacity and how big these factories are. This is still very much unclear at this stage, so it’s very hard to say how much this will add in terms of computing capacity,” he said.
Power consumption is also a key issue. Martens noted that building an AI gigafactory may take one to two years — but building a power generation of that size requires much more time.
“If you want to build a state-of-the-art gigafactory with hundreds of thousands of Nvidia chips, you have to count on the power consumption of at least one gigawatt for one of those factories. Whether there’s enough space in Europe’s electricity grid in all of these countries to create those factories remains to be seen… this will require major investment in power regeneration capacity,” he told CNBC.
UBS forecasts that the current installed global data center capacity of 85 GW will double due to soaring demand. Based on the EU’s 20-billion-euro investment and the plan for each factory to run 100,000 advanced processors, UBS estimates each factory could be around 100-150 MW with a total capacity for all of the facilities of around 1.5-2 GW.
That could add around 15% to Europe’s total capacity — a sizeable boost, even when compared to the U.S., which currently owns around a third of global capacity, according to the data.
Following the announcement of the EU-U.S. trade framework, EU chief Ursula von der Leyen said Sunday that U.S. AI chips will help power the bloc’s AI gigafactories in a bid to help the States “maintain their technological edge.”
“One could argue that it’s relatively easy, provided you have the money. It’s relatively easy to buy the chips from Nvidia and to create these hardware factories, but to make it run and to make it economically viable is a completely different question,” Martens told CNBC.
He said that the EU will likely have to start at a smaller scale, as the region is unable to immediately build its own frontier models in AI because of their expense.
“I think in time, Europe can gradually build up its infrastructure and its business models around AI to reach that stage, but that will not happen immediately,” Martens said.
