Artificial Intelligence & Machine Learning,
General Data Protection Regulation (GDPR),
Next-Generation Technologies & Secure Development
Europe’s Challenges Extend Beyond Regulatory Revisions
A key assumption driving a proposed overhaul of European technology regulations is the belief that excessive bureaucracy hinders the region’s progress in the global artificial intelligence (AI) race dominated by the United States and China. Advocates of the “Digital Omnibus” proposal, recently unveiled in Brussels, aim to streamline existing tech laws by incorporating lighter regulatory measures, hoping this will enable European developers to advance their efforts more swiftly.
While European companies may welcome a reduction in regulatory obstacles, the deeper issue lies beyond mere red tape. There exists a substantial gap between the requirements of modern AI development and the capabilities currently available in Europe. Although the Omnibus may aid in aligning legal frameworks, it cannot bridge these fundamental shortcomings.
According to Nicola Cain, CEO of Handley Gill Limited, a British compliance consultancy, “Large U.S. firms can concentrate significant resources on AI development, while the EU lacks home-grown tech giants to leverage these opportunities effectively.” Presently, only a handful of domestic companies, such as Aleph Alpha and Mistral, are engaged in creating large-scale generative AI models, all facing pronounced structural disadvantages.
A European Commission analysis underscores that these companies require substantial investments to keep pace with U.S. competitors, noting that European capital markets do not sufficiently meet this need, leading firms to seek funding outside the region. This outflow of resources results in ongoing challenges regarding ownership, control, and strategic direction during a time when scale is crucial.
Major players like Microsoft, Google, and Amazon are investing heavily in AI infrastructure, engaging in efforts unmatched globally. Google alone is expected to spend over $90 billion on AI computing capacity by the end of 2025, as reported by Reuters. These staggering investments underscore an ongoing trend where the majority of global private AI funding continues to favor U.S. firms. In 2024, approximately 81% of private AI investments were allocated to U.S.-based companies, as indicated by Air Street Capital’s analysis.
In contrast, Chinese firms find themselves in a position intermediate to Europe and the U.S., with venture capital investments in 2013 reaching $15 billion, compared to $68 billion in the U.S. and $8 billion in Europe. This disparity in capital distribution leads to substantial second-order effects, determining which organizations can bear the high costs associated with large-scale model training and innovate continuously in AI development. Over time, these dynamics create self-reinforcing advantages for capital-rich ecosystems that extend beyond regulatory intervention.
These challenges are not merely regulatory issues; they are fundamentally rooted in a lack of industrial capacity that the proposed Omnibus cannot address. At the core of Europe’s AI predicament is the absence of hyperscale computing platforms. Without deeply capitalized domestic options, European startups rely on U.S. cloud providers for computing resources, limiting innovation.
Even if the Omnibus were to eliminate legal barriers swiftly, the crucial question remains: where will the industrial strength come from to position Europe competitively on the AI frontier? Regulation can facilitate market shaping, but it cannot fabricate the required giants.
Ronan Murphy, Chief Data Strategy Officer at Forcepoint, emphasizes that “the EU is currently grappling with a competitiveness crisis, and the Omnibus can only manage to stop further decline.” While the proposed adjustments are necessary for recalibration, they are not a panacea for Europe’s deeper challenges in the AI domain.
