How is AI reshaping modern network infrastructure? And what role can Europe play?
It’s no secret that there’s been a steep rise in data generation, driven largely by the growth in connected devices, cloud computing, digital services, and new AI technologies. In fact, it’s expected that the volume of global data will rise to 181 zettabytes by the end of 2025.
Behind this data growth are data centres and the advanced chips within them. These facilities have made large-scale data processing and AI training possible, concentrating compute power in key locations. But as AI models grow larger and more distributed, the ability to move large volumes of data quickly and reliably between data centres, regions, and users will be just as important.
This is where digital infrastructure is being put to the test. Without resilient, high-capacity networks, AI workloads face bottlenecks: training times lengthen, inference slows, costs rise, and data locality requirements become harder to meet.
This raises a critical question: How is AI reshaping modern network infrastructure? And what role can Europe play as the central hub in the AI ecosystem?
Let’s start by taking a look at how regional activity is shifting and how data flows are evolving as a result.
The global AI triangle
Crucially, AI isn’t built or scaled in just one geography, so AI has evolved into an interconnected ecosystem that’s underpinned by cross-border data flows. Within this system, three regions stand out as major regional players in the AI ecosystem.
North America
Firstly, North America is the epicentre of AI innovation. Home to many of the world’s leading AI companies and hyperscalers, the region has seen significant investment in large-scale model training and deployment facilities. This is in large part driven by the region’s vast pool of venture capital and a high concentration of top research institutions, drastically accelerating both commercial and academic endeavours.
However, leadership in compute and model development doesn’t necessarily translate into global AI leadership. As models grow larger and more data-hungry, North America’s ability to scale, monetise, and export AI services will depend on international digital infrastructure, and subsea cables in particular.
The Middle East
We’re also seeing the Middle East, notably the UAE and Saudi Arabia, emerging as a strategic AI powerhouse. Through ambitious, sovereign AI strategies, the region is pouring billions into AI infrastructure, skills development, and research. According to Gartner forecasts, tech spending in MENA is expected to reach $169 billion in 2026.
Ultimately, for the Middle East to position itself as an AI producer and enabler, the region will have to rely on ultra-low latency connectivity to large export markets in Europe (and beyond).
The Nordics
Across Norway, Sweden, and Finland, the Nordics play a different but equally important role in the AI ecosystem. By utilising their strength in hydropower, wind, and geothermal energy, plus cooler climates, the region has become a hub for sustainable, energy-efficient data centres.
Natural cooling techniques and access to renewable energy allow the Nordics to support some of the most energy-intensive AI workloads, effectively exporting low-carbon cloud and compute capacity to Europe and global markets.
Whilst North America and the Middle East are driving AI innovation, growth, and investment, think of the Nordics as the region offering behind-the-scenes support to these energy-intensive workloads with sustainable infrastructure.
Europe as the AI exchange hub
Now, what links these three regions is Europe’s position at the centre of them all. Sitting between these regions, Europe has become a critical coordination layer in the global AI ecosystem — one that is structurally impossible to bypass, at that.
The continent is already underpinned by intercontinental cables and DCIs, enabling fast, reliable data transfer at scale. It’s also home to strategic data centre hubs like FLAP-D (Frankfurt, London, Amsterdam, Paris, and Dublin), which are quickly developing to host hyperscale and edge compute.
Europe also has strong regulatory frameworks, like GDPR and the EU AI Act, which provide a harmonised approach to data protection and AI governance. This consistency reduces friction and complexity when data moves across borders within Europe, reinforcing trust and making the region an attractive base for cross-border AI operations.
Turning structural advantage into operational readiness
Europe’s position in the global AI ecosystem isn’t some abstract, aspirational concept – it’s an inevitable outcome that’s shaped by geography, regulation, and existing digital interconnection. As AI workloads become increasingly distributed and latency-sensitive, Europe will increasingly act as the exchange point between where AI is built, where it is powered, and where it is consumed.
To fully realise the opportunity ahead, Europe needs to make a shift from incremental network expansion to deliberate infrastructure design. That means building for resilience over efficiency and long-term demand rather than short-term utilisation. This will require closer coordination between governments and network operators to make sure that infrastructure investment aligns with how AI workloads are actually evolving. Several priorities stand out:
Firstly, governments and operators need to continue investing in new, diverse subsea routes, designing networks for resilience rather than just efficiency. True resilience depends on better route diversity, which could look like new subsea paths that bypass existing choke points, or greater investment in north-south and east-west terrestrial backbones. It also means planning more deliberately for cable damage or outages, whether caused by accidental, environmental, or geopolitical disruption.
At the same time, regulatory processes should evolve to support faster infrastructure deployment. Though Europe’s governance frameworks play a role in building trust, fragmented permitting and slow approval cycles slow the rollout of critical infrastructure projects. Streamlining these processes will be essential if infrastructure deployment is to keep pace with AI-driven demand.
On this note, public-private partnerships will be critical to Europe’s success. No single government or operator can sufficiently prepare Europe’s digital infrastructure alone. By combining public funding with private-sector expertise, Europe can modernise legacy networks, unlock capacity in emerging hubs, and scale infrastructure in a way that is proactive rather than reactive.
Ultimately, Europe doesn’t need to outspend the US on compute or match the Middle East’s state-backed AI ambition to play a defining role in the AI era. Its position is inevitable – provided that private and public organisations prepare for it. By getting subsea and terrestrial networks right, with resilience, diversity, and long-term demand built in, Europe will become the infrastructure layer global AI can’t function without.
