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Published on 19.05.2026 
Siemens established a presence in the Hauts-de-France region in 1983 when it helped develop the world’s first automated subway system in Lille.
Nowadays, the group works with many local companies, such as Lille Airport, ACC, and L’Oréal, and has over 150 employees spread across four locations:
A strong local presence that enables Siemens to work closely with manufacturers, quickly test new technologies—such as artificial intelligence—and accelerate their deployment.
Europe is lagging behind in the development of AI language models. But it’s not too late for it to find a place in practical applications within our economy.
“I am convinced that the countries that master AI will dominate the economy over the next 50 to 100 years.” Doris Birkhofer, Chairwoman of Siemens France
With this in mind, industrial AI represents a powerful driver for competitiveness among European companies.
Its implementation is based on five fundamental needs.
1. Industry awareness of the value of AI in driving competitiveness
Industrialists are not yet fully aware that artificial intelligence is a driver of competitiveness and do not know how to implement AI in their specific fields.
A study conducted by IPSOS at the Industry 2024 global trade show found that attendees ranked AI ninth (out of 10) among the major challenges facing businesses.
It is therefore essential to educate business leaders, help them understand the importance of this technology for their growth and long-term viability, and support them in its implementation.
This last point is Siemens’ mission.
The Group is committed to supporting businesses and implementing tailored, ready-to-use technologies within their organizations, such as predictive maintenance.
2. A wealth of data
“You Europeans are sitting on a gold mine.”
Jensen Huang, CEO of Nvidia
Like all LMM systems, industrial artificial intelligence requires a vast amount of data in order to organize itself and learn.
Yet today, only 20% of industrial data is usable.
This data, which is held by companies (3D drawings, equipment operating manuals, etc.), is neither structured nor clearly organized.
“In a way, 80% of our competitive advantage goes unused.”
Doris Birkhofer, President of Siemens France, at Investor Day 5
Making this data accessible and usable is a key challenge in the development of LMM and sector-specific applications, all of which contribute to competitiveness.
“Our goal is to create industrial LMMs for every sector by bringing together the various stakeholders in the ecosystem and value chain to share data confidentially, while still allowing them the flexibility needed to differentiate themselves from their competitors.”
Doris Birkhofer, Chairwoman of Siemens France
3. Effective infrastructure
“AI can only grow as fast as the infrastructure allows.”
Doris Birkhofer, Chairwoman of Siemens France
To be deployed, AI requires reliable and efficient networks that can deliver the necessary power and provide easy access to data centers and supercomputers.
4. Talented people
Regions must have both people who know how to develop applications using large language models (LLMs) and people who are capable of using them.
“AI can help address labor shortages and provide greater flexibility.” For example, it can help machine operators perform tasks that previously required the assistance of an engineer.”
Doris Birkhofer, Chairwoman of Siemens France
5. Political support
Economic policymakers must recognize the competitive challenges posed by AI and encourage its development.
“Regulations should not hinder the development of AI, but rather encourage it.”
AI is bound to affect certain professions and cause some of them to disappear. In particular, everything to do with transactions and analytics. But it will also bring new ones to the surface. This has been the case in all major industrial revolutions. It is up to us to plan ahead so that we can adapt as effectively as possible to these developments.
On the other hand, there is one thing that worries me a little more: youth employment.
Many young people take on analytical roles to get a foot in the door at companies; they have a hard time finding work. And AI is going to be a major competitor for these young people.
Therefore, it is our responsibility to ensure that they find a job so that they can develop their skills. Because AI isn’t here to replace humans, but to help and support them.
For Siemens, the Hauts-de-France region offers a combination of factors that are rare in Europe and which are particularly suited to the growing role of industrial artificial intelligence.
“Industrial data is a goldmine that you own and need to learn how to tap into.”
Doris Birkofer, Chairwoman of Siemens France, at Investor Day 5
Agri-food, luxury goods, batteries, pharmaceuticals, mobility… The Hauts-de-France region is an industrial powerhouse.
This diverse economic landscape and the skills it encompasses represent a major source of valuable data and industrial expertise that can be used to train AI systems to develop sector-specific applications.
In Hauts-de-France, collaboration isn’t just a slogan. It’s a reality. Local ecosystems are conducive to collaboration and data sharing.
Combined with an entrepreneurial spirit and a strong commitment to continuous improvement, this ability to work together will enable regional businesses to become more competitive through the implementation of automation solutions.
The production of largely carbon-free electricity at competitive costs, along with the availability of land and real estate, is attracting data center projects.
“Hauts-de-France is the third-largest region in France in terms of hosting data centers. You will have access to significant computing power.”
Doris Birkhofer, Chairwoman of Siemens France
This powerful and comprehensive environment is ideal for developing advanced and complex digital solutions such as digital twins, AI models that are integrated into production lines, and smart energy systems.
The Hauts-de-France region offers a wide range of high-quality initial and continuing education programs and is home to leading research centers and training institutions that are dedicated to developing the talent of tomorrow.
For Siemens, the Hauts-de-France region is an ideal testing ground for evaluating its solutions on a large scale before rolling them out to other sites in France or abroad.
A prime example: the L’Oréal factory in Gauchy
Siemens has developed advanced automation solutions for high-volume production there.
🎯Result: The technology tested in the Hauts-de-France region was subsequently replicated at the L’Oréal plant in Mexico City and then in Aulnay-sous-Bois, thereby demonstrating the region’s value as a hub for innovation that can be scaled up globally.
The group has also been involved in other key initiatives in:
In all these cases, the Hauts-de-France region is playing a key role:
A local value chain that drives innovation, serves the community, and positions the region as a leader in the development of industrial AI in Europe.
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