Artificial intelligence is placing unprecedented strain on the infrastructure underpinning modern networks. Computing workloads are shifting toward data centres and edge locations, intensifying requirements for power supply and network capacity to handle the load.
For Nokia, this transformation represents more than a routine technology upgrade. The Finnish vendor sees it as a "network super-cycle" with potential to unlock fresh opportunities across the UK's telecoms sector, though realising those gains will demand more than simply constructing new data centres. The location, management and critical infrastructure supporting AI systems will become increasingly central to success.
Paul Alexander, Nokia's UK Managing Director and VP for Sales for the UK and Ireland, frames AI not as a standalone technology but as a network super-cycle generating fresh demands on telecommunications and infrastructure. "If you think about what AI is and how AI actually gets delivered to people, you're talking about data centres containing large amounts of compute," he explains.
Alexander identifies three essential components for data centre operations: a physical location with computing equipment, sufficient power to operate it, and robust network connectivity linking everything together. "If you don't have the network, you can't transport the data, which is fundamentally what we're talking about here," he states.
This framework opens multiple revenue streams for Nokia within the UK market. Mobile operators continue expanding 5G infrastructure and connecting expanding networks of base stations. Simultaneously, interest is growing in deploying AI computing resources at the network edge rather than centralised locations.
The most significant emerging opportunity, Alexander suggests, involves the networks interconnecting data centres both domestically and across borders.
Distributing the AI grid
Nokia is increasingly promoting the concept of an "AI grid"—a departure from concentrating massive computing resources in a handful of enormous facilities. Instead, AI infrastructure could be distributed across numerous smaller installations.
Consider a data centre consuming 100MW of power. Rather than consolidating all operations at a single site, equivalent computing capacity could theoretically be dispersed across dozens of locations. Alexander contends this approach will "reduce the risk", creating fresh opportunities for telecom operators who already possess buildings, sites and infrastructure assets that could be repurposed as smaller edge data centres.
"They have a lot of that infrastructure set there, doing nothing that they could repurpose for those smaller edge type of data centres," he notes.
Distributing computing across multiple sites introduces a critical new requirement: interconnectivity. "To connect all that together, you need, again, a high-capacity, low-latency optical network," Alexander observes—an area where Nokia identifies substantial commercial potential.
Reshaping industry relationships
AI infrastructure is also transforming how organisations collaborate and interact. "The difference in the AI infrastructure world is that it's much more of an ecosystem than a traditional telecoms network," Alexander explains.
The UK possesses a mature data-centre sector with more than 500 facilities distributed nationwide, positioning the country to capitalise on AI expansion. However, Alexander identifies a significant constraint: the availability of affordable power. He points to Nordic countries, where data centres benefit from abundant renewable energy and lower electricity costs.
"The issues we need to figure out is: how do we get more low-cost, renewable power?" he questions. Addressing this challenge would strengthen the UK's appeal as a destination for data centre and AI infrastructure investment. Alexander adds: "The growing importance of data centres means the lines between telecoms and critical national infrastructure are becoming less clear."
The sovereignty dimension
Questions surrounding where equipment originates, how it operates and from where it is managed are gaining prominence. "Where the equipment is made, how it's managed, where it's operated from – all that kind of stuff. Sovereignty is becoming a critical issue," Alexander states.
Nokia believes its European heritage positions it to address these concerns as governments and enterprises make deliberate choices about where critical AI infrastructure is constructed and controlled. "Nokia is a European vendor. In fact, the only European vendor that is really able to provide the full complement of infrastructure that's needed to underpin AI," he asserts.
For Alexander, the trajectory of AI hinges not on larger data centres or additional GPUs alone. Rather, success depends on the networks that enable the AI grid concept to materialise. "It's going to be in those networks that allow that AI grid concept to come to life," he concludes.
