Executive Summary

• Anders Fryxell, Chief Sales Officer of atNorth, talks about how geography is becoming AI’s biggest competitive advantage; regions that can provide abundant power, resilient infrastructure, political stability and long-term capacity will be positioned best to give an advantage in the AI race.
• Geopolitical tensions are reshaping technology supply chains, and as governments seek greater control over critical digital infrastructure, organisations are paying closer attention to where their AI workloads reside.
• It is fast becoming one of the largest strategic advantages, especially for the regions that combine energy abundance, infrastructure resilience, connectivity and sovereignty.

For much of the past three years, discussions about artificial intelligence have focused on models, algorithms, chips and software innovation. The race to build more powerful AI systems has been framed primarily as a competition between technology companies seeking to develop the most advanced capabilities. However, a new reality is emerging. AI is no longer simply a software development competition, rather a race for access to the infrastructure that powers it.

As organisations across Europe move from AI experimentation to large-scale deployment, geography is becoming a strategic differentiator. The regions that can provide abundant power, resilient infrastructure, political stability and long-term capacity will be best positioned to support the next generation of AI growth.

For AI operators, these factors are time to market, total cost of ownership, scalability, resilience and long-term competitiveness. At the heart of this discussion is a growing recognition that power, rather than compute, is becoming the primary constraint on AI growth.

The energy challenge behind AI

Training and operating advanced AI systems requires extraordinary amounts of energy. Some AI training clusters are now requiring 1GW of power, while the rapid growth of inference workloads is creating sustained demand for high-performance infrastructure capable of operating around the clock.

Across Europe, this demand is colliding with a reality that the data centre industry has been discussing for years: power availability is becoming increasingly scarce. In many traditional European data centre markets, including parts of Germany, Ireland, and the Netherlands, grid constraints are limiting new developments. Securing sufficient power capacity can take years, while energy costs remain subject to market volatility and geopolitical pressures.

These challenges extend beyond simply finding enough electricity, organisations investing in AI infrastructure need long-term predictability. Large-scale AI deployments require planning horizons, often spanning a decade or more, and AI operators need confidence not only that power will be available, but that it will remain economically viable throughout the lifespan of their infrastructure investments.

This is where the geographical location of a data centre begins to shift from being a real estate consideration to a strategic advantage. Access to power is not distributed evenly across Europe and so the ability to scale AI increasingly depends on where infrastructure is located, making geography one of the most important variables in determining future AI capacity.

While many central European markets face mounting constraints, the Nordic region offers a fundamentally different proposition. Countries such as Iceland, Sweden, Norway and Finland benefit from abundant renewable energy resources, robust grid infrastructure and some of the most competitive power markets in Europe. These advantages translate into long-term energy availability and greater price stability – two factors that are becoming increasingly important for AI operators.

The areas that benefit from the resources that AI needs most have a strategic advantage and are emerging as the new hubs for AI-ready digital infrastructure. Few regions in Europe possess all of these characteristics simultaneously, but the Nordics are one of them, which is precisely why atNorth is present in each Nordic country.

Geography is reshaping AI infrastructure

Geography is influencing not only where infrastructure is built, but how AI ecosystems themselves are designed.

Large language training models and other advanced AI systems are highly power-intensive and often less sensitive to latency. These workloads can therefore be located in regions that offer the long term energy availability and stability required to support long term AI growth.

Conversely, inference workloads present a different challenge. As organisations deploy AI-powered services to end users, responsiveness becomes critical. Applications such as conversational AI, real-time analytics and personalised digital experiences require infrastructure located closer to users to ensure low-latency connectivity. These are usually highly connected metropolitan regions that provide proximity to major business centres and population hubs.

Rather than competing directly, these regions are beginning to play complementary roles within Europe’s AI ecosystem. A more distributed data centre landscape is emerging, making location a core factor in urban planning and the development of civic infrastructure.The future of AI infrastructure is therefore unlikely to be concentrated in a handful of locations. Instead, it will consist of interconnected regional ecosystems designed around the specific requirements of different AI workloads.

Sovereignty, security and European competitiveness

The growing importance of infrastructure geography also has broader implications for Europe’s digital future. Governments across the continent are increasingly focused on digital sovereignty and reducing dependence on external infrastructure providers. As geopolitical tensions reshape technology supply chains and governments seek greater control over critical digital infrastructure, organisations are paying closer attention to where their AI workloads reside, who operates the infrastructure supporting them, and which jurisdictions govern access to data and compute.

AI is now widely recognised as a strategic capability that will influence economic growth, innovation and national competitiveness for decades to come. But building sovereign AI capabilities requires more than access to advanced processors. It requires access to reliable, sustainable and scalable infrastructure. A study by the European Data Centre Association (EUDCA) found that data centres make a significant contribution to Europe’s economy, it follows that those regions that can support data centre development sustainably are becoming strategic assets in this landscape.. Their role extends beyond supporting individual organisations; they are helping to create the foundations upon which Europe’s AI ambitions can be built.

This creates an opportunity for policymakers and industry leaders alike. By aligning AI development strategies with regions capable of supporting long-term infrastructure growth, Europe can strengthen both its competitiveness and its resilience.

The next phase of the AI race

The first chapter of AI may well have been defined by algorithms and innovation but the next chapter will almost certainly be defined by infrastructure. As demand for AI continues to accelerate, access to power, land, connectivity and sustainable energy will increasingly determine which regions attract investment and which struggle to keep pace.

For enterprises, hyperscalers and policymakers, this represents a fundamental shift in thinking – the question is no longer simply how to build AI infrastructure but where to build it.

In the years ahead, geography will prove to be one of the most important competitive advantages in the race to operationalise AI, the regions that can combine energy abundance, infrastructure resilience, connectivity and sovereignty are best placed to attract investment and support AI deployment at scale.