In an era marked by high production costs, a shortage of skilled labor, and increasingly aggressive global competition, AI applied to manufacturing represents one of the few concrete levers available to Europe to defend and revive its industrial base.
According to Bloomberg, which dedicated a special report to the topic, thanks to a unique heritage of production data accumulated over more than a century of experience and deep technical expertise, the Old Continent can still carve out a leading role in this field, unlike what happened with generative AI for consumers.
Sensors that regulate the production of Pringles chips in real time in Poland, smart factories in Germany, and almost fully autonomous plants: these are just some signs of a change that, according to the financial publication, could strengthen the continent’s competitiveness and economic sovereignty.
Pringles in Kutno: when AI ensures uniformity
Every day, about 100 million cans of the famous Pringles chips come out of the Kellanova plant in Kutno, central Poland.
Potato harvests are never identical, yet the final product must always offer the same crunchiness and flavor. Here, sensors, lasers, and cameras constantly monitor humidity, protein content, and other factors. The data flows into Siemens software that automatically adjusts the recipe before waste or slowdowns occur.
It is a tangible example of how AI is already transforming real processes, ensuring consistent quality without continuous human intervention.
Europe’s strength
Unlike the United States and China, which dominate AI aimed at the general public, Europe can rely on a valuable resource: a long industrial tradition and a huge amount of data generated in production processes.
This background allows the development of solutions capable of automating entire factories, going beyond the capabilities of simple chatbots.
German Economy Minister Katherina Reiche recently recalled that integrating AI into businesses has become essential to maintain sovereignty, competitiveness, and ultimately the economic future of the region.
Not by chance, according to a recent Interface report, Europe boasts more startups specialized in manufacturing AI than the Americans, while giants like Siemens, Schneider Electric, Dassault Systèmes, and ABB continue to incorporate these technologies into their automation systems.
Increasing pressures
The European industrial sector is navigating difficult waters: expensive energy, an aging workforce, a lack of skilled workers, and Asian rivals rapidly gaining ground.
According to Sabine Scheunert of Dassault Systèmes, there may be only two or three years left to seriously integrate AI into production processes, otherwise the gap with Asia will become unbridgeable.
Christian Bruch, CEO of Siemens Energy, confirms that in Asia new technologies are adopted faster, as demonstrated by the automated plant in Shanghai where many tasks have already shifted from human hands to machines.
Real applications
Industrial AI applications are already numerous. Predictive maintenance analyzes historical data to anticipate failures and avoid production downtime. In quality control, Trumpf uses intelligent scanners to check the edges of laser-cut sheets and adjust settings on the fly.
More ambitious visions, however, aim at so-called “dark factories,” plants almost devoid of human presence, managed by AI agents and robots. Building them requires significant investments, specialized skills, and already standardized processes—requirements not all European companies possess.
The Trumpf case
Trumpf offers a concrete example of what can be achieved through automation processes.
By connecting machines, it has gained up to 30% efficiency and today manages smart factories in several countries, including the United States and China. In its Ditzingen plants, autonomous robots transport components between work islands, while operators oversee everything in tidy and clean environments.
Yet, economic returns are mainly seen in the medium term, and in times of tight margins, not all companies are ready to invest on a large scale.
SMEs’ difficulties and scalability issues
For most SMEs in the German Mittelstand and across Europe, the situation is more complex.
Paul Walczok, who runs a small company of 12 people near Munich, has automated several stages but believes that specialized human intervention remains indispensable in the final processing. Small batch productions often make full automation uneconomical.
Even in large groups, scalability is complicated: different methods and processes between plants in Hungary and Portugal make it difficult to standardize solutions, as explained by Cecile Vercellino of Schneider Electric. Only 30% of companies derive real benefits from extensive digital transformation projects.
Sensitive data and sovereignty
Detailed information on machines, materials, and processes represents a strategic asset. European companies are cautious about sharing them with external suppliers, especially American or Chinese ones, and this could favor the development of European solutions if the opportunity is seized.
Meanwhile, China is accelerating at the intersection of robotics and AI, while the United States advances with companies like Emerson, Rockwell, and Honeywell.
The Boston Consulting Group estimates the manufacturing value at risk of offshoring from Western Europe and Nordic countries at about one trillion dollars if productivity does not improve significantly.
