GREÏ: Europe races to build its own AI backbone
Recent outages across global cloud infrastructure have once again served as a reminder of how deeply Europe depends on foreign hyperscalers. When platforms run on AWS or services protected by Cloudflare fail, European factories, logistics hubs, retailers, and public services can stall instantly.
U.S.-based cloud providers currently dominate Europe’s infrastructure landscape. According to market data, Amazon, Microsoft, and Google together control roughly 70% of Europe’s public cloud market. In contrast, all European providers combined account for only about 15%. This share has declined sharply over the past decade. For European enterprises, this means limited leverage over resilience, performance, data governance, and long-term sovereignty.
This same structural dependency is now extending from cloud infrastructure directly into artificial intelligence and its underlying investments. Between 2018 and 2023, U.S. companies attracted more than €120 billion in private AI investment, while the European Union drew about €32.5 billion over the same period.
In 2024 alone, U.S.-based AI firms raised roughly $109 billion, more than six times the total private AI investment in Europe that year. Europe is therefore trying to close the innovation gap while simultaneously tightening regulation, creating a paradox in which calls for digital sovereignty grow louder even as reliance on non-European infrastructure deepens.
The European Union’s Apply AI Strategy is designed to move AI out of research environments and into real industrial use, backed by more than one billion euros in funding. However, most of the computing power, cloud platforms, and model infrastructure required to deploy these systems at scale still comes from outside Europe. This creates a structural risk: even as AI adoption accelerates inside European industry, much of the strategic control over its operation may remain in foreign hands.
Why industrial AI is Europe’s real monitoring ground
For any large-scale technology strategy to succeed, it must be tested and refined through real-world deployment, not only shaped at the policy level. The effectiveness of Europe’s AI push will ultimately depend on how quickly new rules, funding mechanisms, and technical standards translate into working systems, and how fast feedback from practice can inform the next iteration.
This is where industrial environments become especially important. They produce large amounts of real-time data, and the results of AI use are quickly visible in productivity and cost. As a result, industrial AI is becoming one of the main testing grounds for Europe’s AI ambitions. The companies applying AI in practice will be the first to see what works, what does not, and what needs to be adjusted.
According to Giedrė Rajuncė, CEO and Co-Founder of GREÏ, an AI-powered operational intelligence platform for industrial sites, this shift is already visible on the factory floor, where AI is changing how operations are monitored and optimized in real time.
“AI can now monitor operations in real time, giving companies a new level of visibility into how their processes actually function. I call it a real-time revolution, and it is available at a cost no other technology can match. Instead of relying on expensive automation as the only path to higher effectiveness, companies can now plug AI-based software into existing cameras and instantly unlock 10 to 30% efficiency gains.”
She adds that Apply AI reshapes competition beyond technology alone. “Apply AI is reshaping competition for both talent and capital. European startups are now competing directly with U.S. giants for engineers, researchers, and investors who are increasingly focused on industrial AI. From our experience, progress rarely starts with a sweeping transformation. It starts with solving one clear operational problem where real-time detection delivers visible impact, builds confidence, and proves return on investment.”
The data confirms both movement and caution. According to Eurostat, 41% of large EU enterprises had adopted at least one AI-based technology in 2024. At the same time, a global survey by McKinsey & Company shows that 88% of organizations worldwide are already using AI in at least one business function.
“Yes, the numbers show that Europe is still moving more slowly,” Rajuncė concluded. “But they also show something even more important. The global market will leave us no choice but to accelerate. That means using the opportunities created by the EU’s push for AI adoption before the gap becomes structural.”