As U.S. cloud providers expand sovereign offerings in Europe, new analysis questions whether true data independence is achievable
NEW YORK CITY, NY / ACCESS Newswire / April 21, 2026 / According to new analysis from Ramsey Theory Group CEO Dan Herbatschek, the concept of “sovereign cloud” may offer a false sense of security-and what the firm is calling a growing “sovereignty gap.”
The global race for AI dominance is no longer just about models-it’s about who controls the infrastructure beneath them. As U.S. cloud providers expand deeper into Europe with sovereign cloud offerings, enterprises are facing a growing tension between innovation, compliance, and control.
“Sovereign cloud is a step forward, but it doesn’t solve the core issue,” said Dan Herbatschek, CEO of Ramsey Theory Group. “You can localize infrastructure, but you cannot localize jurisdiction. That is the fundamental tension enterprises need to understand.”
The surge in sovereign cloud adoption is being driven by a convergence of forces: a rapid increase in AI workloads, mounting regulatory pressure across the European Union, and the continued dominance of U.S.-based hyperscalers such as Amazon Web Services, Microsoft Azure, and Google Cloud. Together, these dynamics are accelerating enterprise reliance on platforms that may not fully align with regional data sovereignty expectations.
However, the risks extend beyond data residency.
Ramsey Theory Group warns that enterprises may be underestimating the implications of legal jurisdiction and control. U.S.-headquartered cloud providers remain subject to regulatory frameworks such as the CLOUD Act, which can introduce ambiguity around data access-even when data is stored within European borders. This creates potential exposure across compliance, governance, and long-term operational strategy.
“Enterprises think they’re solving for compliance-but they may be hardcoding dependency into their future,” Herbatschek added.
The firm also highlights the growing risk of vendor lock-in across both infrastructure and AI layers, as organizations increasingly build data pipelines, models, and decision systems directly on top of hyperscaler ecosystems. As AI becomes more deeply embedded into enterprise operations, control over infrastructure is quickly becoming synonymous with control over intelligence.
“This isn’t just about where your data sits,” said Herbatschek. “It’s about who ultimately has authority over it-and how that shapes your ability to operate, compete, and adapt.”
In the AI era, the stakes are significantly higher. Data is no longer static-it fuels models, which in turn drive decisions. As a result, infrastructure choices made today can define how organizations operate for years to come.
“This isn’t an IT decision anymore-it’s a board-level question about control, risk, and long-term competitiveness,” Herbatschek said.
Ramsey Theory Group advises enterprise leaders to take a more strategic approach to cloud and AI infrastructure decisions, including:
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Evaluating jurisdictional exposure, not just data location
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Prioritizing multi-cloud and interoperability strategies to reduce dependency
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Involving legal, risk, and executive leadership early in infrastructure planning
As global competition around AI intensifies, the firm believes enterprises that proactively address sovereignty and control will be better positioned to scale securely and sustainably.
Visit https://www.ramseytheory.com/ to learn more about Ramsey Theory Group.
About Ramsey Theory Group
Ramsey Theory Group is a New York-based technology and innovation firm specializing in enterprise AI, cybersecurity, and decision intelligence. Led by CEO Dan Herbatschek, the company develops scalable technology platforms serving healthcare, construction and field services, logistics, automotive retail, creative and digital infrastructure markets. With operations in Los Angeles, New Jersey, and Paris, Ramsey Theory Group focuses on AI-driven innovation, operational resilience, and long-term enterprise growth across complex, real-world industries.
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SOURCE: Ramsey Theory Group
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