Europe’s digital infrastructure is entering a turning point. As U.S. cloud providers continue to dominate the continent’s computing backbone and attract far greater investment in artificial intelligence (AI), the European Union is now accelerating efforts to build its own capability. Through the Apply AI Strategy, the EU aims to shift AI from research environments into real industrial operations and establish a foundation for next-generation, European-owned critical technology infrastructure.
Recent global cloud outages have highlighted the issue with new clarity. When services running on Amazon Web Services or protected by Cloudflare stall, European factories, logistics networks, retailers, and public services can be disrupted within minutes. For many organisations, these interruptions reaffirm how dependent Europe has become on foreign hyperscalers and how limited its control is over resilience, performance, and data governance.
The numbers illustrate the structural imbalance. Amazon, Microsoft, and Google control around 70% of Europe’s public cloud market. All European providers combined hold about 15%, a share that has declined steadily over the past decade. This concentration is now extending into AI, where the reliance on U.S. investment and infrastructure is shaping how European organisations access compute, develop models, and deploy operational AI systems.
Between 2018 and 2023, U.S. companies secured more than €120 billion in private AI investment. Over the same period, EU companies raised roughly €32.5 billion. In 2024 alone, U.S.-based AI firms attracted around $109 billion in investment, more than six times the total private AI investment in Europe. The continent is therefore attempting to advance AI adoption while also tightening regulation, creating a difficult balance as calls for digital sovereignty grow louder.
The Apply AI Strategy seeks to address this gap by supporting the deployment of AI in real production environments. Backed by more than one billion euros in funding, the initiative is designed to help organisations move beyond pilot projects and integrate AI into day-to-day operations. Yet the compute resources, cloud platforms, and foundational model infrastructure needed to scale these systems often remain outside Europe. As a result, even as European industries accelerate AI adoption, strategic control over core technology layers may continue to sit abroad.
Industrial AI as Europe’s proving ground
The success of any large-scale technology strategy depends on practical deployment. Policies, standards, and funding frameworks only become meaningful when they are tested through real operations. For Europe’s AI strategy to deliver impact, the process of learning, adjustment, and improvement must come from real industrial use.
Industrial environments are central to this process. Production sites, logistics hubs, and processing plants generate vast amounts of real-time operational data. When AI tools are deployed in these environments, their outcomes, such as increased throughput, reduced downtime, or improved energy management, are quickly visible. This makes industrial AI one of the primary testing grounds for Europe’s emerging AI ecosystem.
Giedrė Rajuncė, CEO and Co-Founder of GREÏ, an operational intelligence platform for industrial sites, notes that this shift is already taking place across the sector. AI systems are beginning to monitor operations in real time, changing how organisations view and manage their processes. According to Rajuncė, real-time visibility allows industrial operators to achieve efficiency gains without making large investments in new automation equipment. By integrating AI software into existing camera networks, organisations can uncover performance improvements of between 10% and 30%.
Rajuncė also highlights a wider competitive shift. Apply AI is influencing how companies attract talent and capital, with European startups now competing directly with U.S. firms for engineers, researchers, and investors who are increasingly focused on industrial AI. She observes that progress often begins with solving one specific operational challenge. When real-time AI tools address a clear problem and deliver measurable value, confidence grows and return on investment becomes easier to demonstrate.
Data from across the EU indicates that adoption is increasing, though at a cautious pace. Eurostat reports that 41% of large European enterprises had implemented at least one AI-based technology by 2024. On a global scale, a McKinsey & Company survey shows that 88% of organisations worldwide are already using AI in at least one business function.
For Rajuncė, the implications are clear: the global market is moving quickly, and Europe will have to accelerate if it wants to remain competitive. The Apply AI Strategy gives organisations a structured opportunity to test operational AI tools, build internal capability, and reduce reliance on non-European infrastructure. The key will be turning these opportunities into practical deployments that strengthen Europe’s position in industrial AI.
Building Europe’s next technology foundation
The race to establish Europe’s AI backbone is no longer theoretical. It is unfolding across factory floors, logistics lines, energy networks, and other operational environments where AI can deliver measurable value. The Apply AI Strategy provides a crucial platform for deploying these systems, but Europe still faces strategic challenges around compute capacity, investment, and infrastructure ownership.
To reduce long-term dependency, Europe will need to grow its domestic cloud capacity, expand its AI investment ecosystem, and support the development of industrial AI platforms that operate on European terms. The momentum behind industrial deployment offers a clear path forward. Each successful use case brings Europe one step closer to a home-grown technological foundation that supports both competitiveness and sovereignty.
The pace of global AI adoption leaves little room for delay. Europe now has an opportunity to strengthen its position by deploying AI in real operations, learning from early adopters, and building infrastructure designed for long-term resilience and independence.
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