The Point: European CEOs must prioritize AI sovereignty through hybrid infrastructures, scaling across all company sizes, and talent investments as productive capital equally.
European business leaders must accelerate in four areas to keep pace with AI development: strategic sovereignty, scalability across all company sizes, security and sustainability. The debate in Europe has shifted from theoretical considerations to practical implementation questions.
Sovereignty through Hybrid Approach: European organizations need choices rather than isolation. According to current analyses, approximately one-third of enterprise workloads require stronger control over data, models and infrastructure. The remaining third benefits from access to global expertise and economies of scale. Europe can build on established champion companies such as ASML (hardware), SAP (software) and Siemens as well as Dassault (industrial AI). With 19 already operational EU AI Factories and plans for up to five EU Gigafactories, the continent has concrete infrastructure. The EU Tech Sovereignty Package should reflect this hybrid path.
Scaling across Small and Medium-Sized Business Segment: While large European companies are making progress with AI scaling, there is a significant gap compared to North America — particularly pronounced among smaller companies. The “long tail” of mid-market businesses faces specific barriers: capital raising, skilled labor shortages and technology access. Approximately half of AI engagements currently focus on productivity improvement; meanwhile, one-quarter focus on growth acceleration, compared to 15 percent a year ago. Studies of the top 3,000 organizations worldwide show: European companies are catching up — particularly in upskilling and process optimization.
Investment in Talent Development as Productive Capital: A common misallocation lies in unbalanced capital distribution: capital flows to infrastructure while cultural change and incentives for middle management fall short. Experts propose treating employee training analogously to research and development as an investment in productive capital, not as an operating expense. This requires realignment of budget priorities and performance metrics in organizations.
Source: www.politico.eu · Published 9 July 2026
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