Europe is still lagging badly in the AI race. U.S. private investment in AI rose to $285.9 billion in 2025, according to Stanford University figures, while Europe drew $20.9 billion. The U.S. also has higher adoption rates, more data centers and the world’s most valuable AI companies.
Peter Koerte, CEO of Siemens’s Smart Infrastructure division, sees one possible opening for Europe: industrial AI. Siemens’s Industrial Foundation Model is still in development, but Koerte says it could shorten engineering cycles by up to 40%. Siemens plans to invest more than €1 billion in industrial AI over the next three years.
Koerte argues that industrial models have a different edge from large language models because they are trained on manufacturing and engineering data. In his words, 'in engineering, you need to be precise.' He says LLMs do not work well in engineering and production because 'words are much more imprecise.'
Europe’s long industrial history may also help. Koerte says more than half of the companies on the Fortune 500 Europe are over 100 years old, giving the region a large installed base of data in pharma, automotive and chemical companies that have operated there for decades. But he also says persuading companies to share that data is difficult, since firms like BMW or AstraZeneca will not put it on the internet.
Siemens is trying to win trust through long relationships and data controls. Koerte says companies retain ownership of their data, and the data is used only for training. He says Siemens’s decades-old ties with many customers matter because they trust the company to take care of sensitive information.
Talent remains another obstacle. U.S. institutions employ 59% of the world’s elite AI researchers, according to research platform MacroPolo Archive’s Global AI Talent Tracker. Siemens has responded by hiring Vasi Philomin, formerly Amazon’s vice president of generative AI, and Manu Parbhakar, a former Amazon Web Services director. Koerte says, 'you have to write a bigger check than you usually would in Europe.'
The company is also working with Nvidia on an industrial AI operating system. At the same time, the European Commission is pushing for less dependence on American Big Tech. The EU relies on non-EU countries for 80% of its digital infrastructure and services, and the Commission’s tech sovereignty package aims to support homegrown alternatives.
The numbers come first. Europe cannot legislate its way into AI leadership when capital, talent and scale are already concentrated elsewhere. What it can do is stop treating industrial data like a museum piece and start treating it like productive capital. If Siemens is right, the region’s best shot is not matching Silicon Valley model for model, but using its manufacturing base to turn legacy into leverage.
