Much of the global conversation around AI has focused on building increasingly powerful models. Yet the long-term impact of AI will depend on how widely those models are deployed.

AI systems are already powering customer service tools, industrial automation and logistics networks, with adoption accelerating across sectors such as finance and healthcare. As these systems move into production environments, they must operate continuously and reliably across large-scale infrastructure.

This shift places new demands on the computing platforms that power cloud environments. Running modern AI workloads requires infrastructure that can deliver high-performance, predictable scaling, and the efficiency needed to support large volumes of inference requests.

For many European organizations, the key question is no longer who builds the models. It is where those systems can run securely, efficiently, and at scale.

Europe already has a growing ecosystem of regional cloud providers supporting enterprises and public sector organizations across the continent. The demand for their services is only expected to grow, with a recent Gartner forecast estimating that sovereign cloud spending will almost quadruple from the end of 2025 to the end of 2027. As part of this, sovereign cloud IaaS spending will shift 20% of current workloads from global to local cloud providers, and 80% of the spend will come from net new digital solutions or legacy workloads waiting to be migrated to a cloud environment.

Local providers play an important role in delivering infrastructure environments that align with European regulatory frameworks and operational requirements. They also provide organizations with the ability to run workloads locally when data residency, security, or operational considerations require it.

As AI adoption accelerates, regional cloud providers will become increasingly important to organizations that need the ability to run AI systems within European infrastructure.

The next challenge will be ensuring that this ecosystem can keep pace with the infrastructure demands of AI.

Running modern AI workloads demands more than traditional cloud infrastructure. It requires modern computing platforms designed for high-throughput workloads, efficient scaling and the ability to handle large volumes of inference requests as AI systems become embedded across everyday services.

In several cases, regional providers have already begun deploying newer processor architectures designed for modern cloud workloads, helping them deliver greater efficiency and scale as AI adoption accelerates. Continuing to expand access to these platforms will allow regional providers to scale their services, invest in new data center capacity, and support a broader range of AI-driven applications.

Ensuring that these technologies can be deployed locally will allow enterprises and public sector organizations to run AI systems within infrastructure environments that align with their regulatory, operational and security requirements.

Strengthening Europe’s cloud ecosystem means ensuring that regional providers have access to the modern computing platforms needed to support the next generation of AI applications. Ampere® is working with a number of these local providers to enable Arm-based sovereign deployment in the cloud, helping them deliver the performance, efficiency, and scale needed for AI to run securely within Europe.

In the AI era, sovereignty will depend not only on policy and regulation, but on whether the modern compute infrastructure exists to run these systems where they are needed most.

Related:Ampere Expands European Footprint With Broad New Cloud Deployments