Artificial intelligence (AI), and the growing usage of IoT devices, edge and cloud computing applications continue to drive unprecedented changes to the UK data centre market. Industry research from August 2025 indicates that just under half of all new data centres being built within the country will be dedicated to AI, including infrastructure specifically designed to support the necessary training and workloads. These new facilities are characterised by specialist hardware, and significant power demands due to the sheer throughput of data.
Yet as throughput increases, so too does the demand for inter and intra connectivity, and operators now find themselves under pressure to rethink their entire network architecture. It’s pivotal that ultra-low-latency pathways and scalable high-bandwidth links are now prioritised if operators are to keep pace with current and future AI-driven data flows.
The growing data challenges
When training AI models, tasks are split across a significant number of processors within network infrastructure, all of which are likely sharing information on a continuous basis. As a result, throughput and inter/infra connectivity demands increase, and huge volumes of internal data – far beyond the amount traditional enterprise systems require – are consistently on the move within the network.
Additional pressure is also placed on the physical make-up of these data centres as even the smallest of bottlenecks in cable routes or switch capacities can impact data delivery. This makes seamless interconnectivity critical within any network. Therefore, operators now require faster, flatter, and more responsive networks where ultra-low latency and high bandwidth between machines is crucial. No single point in the network should slow down the rest of the system, otherwise the impact could be seismic.
Building and enhancing networks
Thankfully, the next generation of high-speed data links are currently being integrated into these networks in order to support these overburdened operators. For example, from 400G up to 1.6T networks, many high-speed optical links can maintain high-bandwidth connectivity between GPUs and servers to ensure large AI clusters are consistently fed.
These high-capacity links allow data to move more efficiently across the data hall, while helping to prevent slowdowns that can stall and congest networks. Scalability is also optimised, since operators now have the ability to add more high-speed connections, enabling the expansion of AI workloads.
Over 88% of organisations say they now use AI in at least one business function. However, there remains concrete fears that capacity will continue to struggle keeping up with increasing demands. Compounding this issue is the pressure for faster deployments, leaving a lack of time or resources to build the intricate systems that facilitates networks for AI. This has led to third-party system integrators growing in prominence within the market. These businesses are being trusted to handle network building on behalf of the operators, developing their own strategies and turn-key solutions to bolster and quicken data centre deployments and enhancements.
The benefits of OEM alternatives
For cost-effective, high-performance networks, one solution these builders should consider is OEM alternative transceivers. Perhaps the unsung hero behind the ongoing optimisation of networks within the AI revolution, these transceivers are creating, shaping, transmitting and receiving the high-speed optical signals that modern networks rely on.
Historically, enterprise data centres have been dependent on optical components offered by Original Equipment Manufacturers (OEMs), owing to their market dominance and brand reputations. However, with operators now in immediate demand for more flexible procurement paths, OEM alternative suppliers can play a key role in delivering maximised network infrastructure.
OEM alternative solutions providers, such as AddOn Networks, now provide components that offer the same level of quality and performance as OEMs, but at a lower cost for integrators and builders to obtain. These ‘plug and play’ optical components are designed to be interoperable with common switches designed by OEMs, having been rigorously tested within these technologies before sale – meaning they’re an ideal fit for AI data centres looking to quickly implement solutions within its infrastructure. Consequently, leading alternative solutions will work alongside products offered by companies like Nvidia, Arista and Juniper, to name a few.
A partner, not a competitor
For those concerned over void warranties, the use of OEM alternatives is backed by legislation across Europe and North America, which protects businesses from anti-competitive behaviour. As such, and explicit or implicit ‘warranty tie’ suggested by OEMs are illegal.
In fact, the growing presence of OEM alternative transceivers shouldn’t be seen as a threat by market leaders. Instead, they should be seen as a trusted partner, with solutions designed to complement products offered by OEMs and deliver optimal networks. Considering 100 new AI data centres are to be built within the UK by 2030, partnerships between OEMs and these new alternative vendors may be the best option to handle the huge surges in data volumes within networks going forward.
