Why EU CSPs must launch GPU clouds for sovereign AI
The GPU-as-a-Service market is $8.2 billion today. MarketsandMarkets puts it at $26.6 billion by 2030 – a CAGR of 26.5%, one of the fastest-growing infrastructure categories on record.
That is not just a market prediction, it's a pipeline – and it might be conservative. By some estimates, we could be looking at $130bn by 2030 (AnalysysMason).
One thing is clear. Right now, the EU portion of it does not have an owner.
Here is the uncomfortable truth for most EU cloud service providers: the customers you already serve are running AI workloads somewhere. If it is not on your infrastructure, it is on AWS, Azure, or a neocloud you have never heard of.
The GPU cloud category is being built with or without regional providers. The only question is whether EU CSPs show up while the market is still open, or arrive later to compete against incumbents who moved first.
The case for moving now is not complicated. But it does require understanding three things that most CSP conversations miss.
Inference changes everything, and most CSPs haven't caught up
Everyone assumed GPU cloud was a hyperscaler game. For training, they were right.
Training frontier AI models requires tens of thousands of GPUs running in tightly coupled clusters for weeks at a time. That is AWS territory. No regional CSP was going to compete for that.
But training is not where the market is going. Inference is.
Inference is what happens after a model is trained – every time a user gets a response, a document gets summarized, a recommendation gets generated. It runs continuously, at distributed scale, close to users. It does not need a 10,000-GPU hyperscale cluster. It needs reliable, low-latency GPU endpoints that run 24 hours a day.
The shift is already underway and the numbers are decisive. Gartner projects 55% of AI-optimized infrastructure spending supports inference workloads in 2026, rising to 65%+ by 2029. McKinsey puts inference demand growing at 35% CAGR through 2030 – faster than training, faster than traditional compute. By 2030, inference alone will account for more than 40% of total global data center demand.
This is not a niche workload. It is THE workload. And, it is structurally suited to exactly what EU CSPs already operate: sovereign, latency-sensitive infrastructure, close to end users, running in jurisdictions that matter.
The hyperscaler dominance in AI infrastructure is real, but it is training-era dominance. Inference opens the map. EU CSPs are sitting on exactly the right infrastructure profile at exactly the right moment – but most of them are watching it happen from the sidelines.
Compliance is not a constraint. It is a product.
Here is something hyperscalers cannot fix with a press release.
EU enterprises are not just shopping for cheap GPU clouds. They are shopping for GPUs they are legally allowed to use for their workloads. Those are different markets.
GDPR restricts how personal data moves outside the EU. The EU AI Act – now in full enforcement for high-risk systems – creates documentation, auditability, and transparency requirements that are materially easier to satisfy on infrastructure you control and can verify. Get it wrong and you are looking at penalties up to €35 million or 7% of global revenue. Stack GDPR and the AI Act together and a single compliance failure can reach 11% of global turnover.
The result: 20% of European companies have already begun repatriating business-critical data to local facilities. 61% of Western European CIOs are now actively prioritising local cloud providers: not out of preference, but out of board-level risk management.
And here is the part that the hyperscaler sovereign cloud announcements miss. Choosing a European region on AWS addresses data residency – where the server physically sits. It does not address data sovereignty – who controls the infrastructure and under whose law it operates. The US CLOUD Act means that data held by US-headquartered entities remains subject to US legal jurisdiction regardless of where the rack is. For defence contractors, financial institutions, healthcare systems, and public sector agencies, that distinction is not theoretical. It is the deciding factor.
EU CSPs don't have this problem. They are European entities, operating European infrastructure, under European law. That is not a compliance checkbox. That is a genuine competitive moat, one that AWS cannot replicate with a €7.8 billion investment announcement, however large the number.
The sovereign cloud market is projected to grow from $154 billion in 2025 to $823 billion by 2032. North America currently holds 88% of neocloud GPUaaS revenue. That share drops to 72% by 2030 as sovereign cloud initiatives build out in Europe and beyond. That redistribution does not have a predetermined winner. It goes to whoever has built credible sovereign GPU infrastructure when enterprise procurement opens in force.
GPU economics: what is actually true and what isn't
GPU cloud is a large market. Whether it is automatically a good business depends entirely on one variable: utilization.
H100 on-demand pricing across providers currently ranges from under $2/hr on spot neocloud instances to $6.88/hr on AWS and $12.29/hr on Azure – a six-fold spread depending on provider, commitment model, and availability.
An H100 costs $25,000-$30,000 to buy. At $2/hr rental, you need roughly 12,500 hours of billable time to recover the hardware cost alone, before power, cooling, depreciation, or operations. The operators making strong margins on GPU cloud are doing so because they have solved the utilization problem.
The customers who make the economics work are enterprises with compliance requirements, public sector agencies with data residency mandates, and platform companies with consistent inference workloads running 24 hours a day. These buyers are less price-sensitive, sign larger contracts, and churn at structurally lower rates.
The EU players who moved early, and what they understood
The EU CSPs already in the GPU cloud did not wait until they had the perfect product. They moved on to a specific segment with a minimum viable offer and built from there.
- Intronet added to its web hosting and enterprise cloud brands with Aivity – a sovereign AI/LLM hosting service in Switzerland.
- Scaleway secured first-to-market European availability of NVIDIA's Blackwell Ultra B300 GPUs and positioned it explicitly around sovereign compliance.
- OVHcloud published reference architectures for deploying large-scale AI models in sovereign EU infrastructure.
- STACKIT built the GPU offering as a natural extension of its compliance-first positioning into German enterprise and public sector.
Different entry points. Different customer segments. Same underlying insight: the GPU market in Europe is not won on hardware specs. It is won on trust, proximity, and legal clarity.
The window is open. It will not stay that way.
Europe's data center GPU market stood at $10.6 billion in 2024. It is projected to reach $82.2 billion by 2034 (ResearchAndMarkets). The CSPs who move in the next twelve months will be operating from a structurally different position than those who move in twenty-four.
hosted.ai provides the GPUaaS software platform to accelerate your sovereign AI cloud deployment. Just get in touch for a demo or a chat with our team.
