There are few certainties in life: death, taxes and massively increased workloads on infrastructures through the unstoppable rise of AI.
And enterprises and connectivity providers know only too well that AI has fuelled an unprecedented surge in network demand. Keeping pace with the next wave of AI growth will require new long-haul networks to enable the rapid scaling of capacity needs in both existing and emerging enterprise setups – especially within datacentres.
The emergence and widespread adoption of agentic AI-enabled applications is reshaping datacentre requirements, prompting a rapid evolution in networking solutions. AI is driving these advancements, with a dual opportunity for network innovation and operational transformation.
Research earlier in 2025 found that core fibre investment is key to future AI growth, but four-fifths of firms delay builds because of network infrastructure constraints. In addition, global network connectivity provider Zayo predicted AI-driven datacentre capacity to grow 2-6X over the next five years while optical comms technology provider Ciena reported that AI capacity doubling every six months, with hundreds of fibres connected to datacentres being lit up.
Looking at the networks of the future, in October 2025 Cisco noted that two major forces are starting to reshape the landscape: AI agents, which raise the bar for scale, security and governance; and AI infrastructure debt, the early warning signs of hidden bottlenecks that threaten to erode long-term value.
Assessing in April 2025 how to solve these issues, leading research firm Omdia observed that to drive the continued growth of the global AI economy, networks will need to evolve significantly to deliver enhanced capabilities. New, advanced optical networks, it said, were necessary to meet advanced application and service requirements and address surging capacity needs within tight capex targets.
As well as supporting business agility to match bandwidth supply to service utilisation, these new nets – such as all photonic networks – also offer with lower power consumption per bit to meet sustainability goals and reduce energy costs.
And, perhaps most importantly, the benefits of AI in networking can’t be realised fully without considering networking for AI.
Here are Computer Weekly’s top 10 networking stories of 2025.
Just as AI offers a substantial increase in business efficiency and effectiveness, it also places challenges on the network, necessitating increased network and operational innovation. With such dynamics in mind, Nokia is expanding and enhancing its datacentre networking portfolio to meet the increasing performance and scalability demands of connecting AI workloads.
Furthermore, the comms tech company believes that it is able to do this while taking advantage of AI to drive efficiency and reliability into operations.
Datacentres, the cloud and graphics processing units (GPUs) dominate much of the tech sustainability conversation currently due to their vast energy needs. However, it’s the network infrastructure – including routing, interconnects and protocols – that is becoming the real bottleneck as AI workloads increase, due to heat output, cost and energy usage.
AI workloads put a considerable amount of pressure on networks as they are very different from traditional and predictable consumer and cloud traffic, such as streaming and web browsing. AI workloads such as large model training require high-bandwidth, persistent east-to-west traffic. This has led to a key question: can European infrastructure companies scale AI operations sustainably?
Building on its enterprise network architecture, Cisco has embarked on a plan to modernise its campus, branch and industrial networks for the AI era with systems designed to simplify operations across campus and branch deployments such as network configuration
Cisco believes the new products can simplify operations, scale for evolving business needs and enhance security – all critical for unlocking the full potential of enterprise.
The upgrades follow the launch of the IT and networking giant’s AI-ready secure network architecture for enterprises earlier in 2025. They are fundamentally designed to deliver automated deployment and security across highly distributed networks in minutes instead of months, meeting the high-bandwidth, ultra-low latency and intelligent traffic management demands of distributed AI workloads that are increasingly moving to the enterprise edge.
Research has found that “pacesetter” companies are significantly more likely to move network AI pilots into production, and 50% more likely to report measurable value from AI.
The Cisco AI readiness index 2025 revealed that while the AI genie is out of the bottle for organisations for all sizes, only 13% of businesses are fully prepared for it, with those ready as much as four times more likely to move pilots into production and 50% more likely to see measurable value.
Cisco added that the combination of foresight and foundation is delivering real, tangible results at a time when AI agents and AI infrastructure debt were starting to reshape the tech landscape.
As businesses integrate AI into more applications, demand for high-speed, low-latency, secure networks has surged, but a study from IDC has revealed that legacy infrastructure is no longer sufficient to support the scale and complexity of current, never mind future, AI workloads, and emphasises that network modernisation is crucial to ensuring AI success.
The study highlighted how networks were seen as the critical foundation empowering AI-driven growth. More than 78% of companies regarded networking capabilities as either important or very important when selecting providers for GenAI infrastructure, underscoring the need for networks that can handle and secure ever-scaling AI workloads while running complex AI training, inference and storage clusters with ease.
Research from RtBrick has warned that network operators are at risk of being “overwhelmed” by the demands of AI and streaming services on bandwidth in the next five years.
The carrier routing software provider’s study identified issues regarding not just technology but also people and processes. Consumer expectations were rising faster than the networks designed to meet them and despite significant investment in AI, operators admitted they can’t fully optimise networks without access to more real-time data and network modernisation delayed through staff issues.
There are few industries these days that are not influenced by AI. Networking is very much one of them. It is barely conceivable that any network of any reasonable size – from an office local area network or home router to a global telecoms infrastructure – could not “just” be improved by AI.
In other words, the implementation of AI results in operational efficiencies, increased reliability and user benefits. But as we know, nothing in life is simple, and to guarantee such gains, AI can’t be “just” switched on.
A progress report from metro and long-haul data connectivity firm Lumen Technologies has shown a quickening in pace in its network expansion to meet massively increasing workloads, including new fibre miles, added network capacity and coast-to-coast US build.
Altogether, Lumen said it has delivered “significant” progress in its mission to build the backbone for the AI economy, delivering the capacity upgrades and high-speed connectivity enhancements needed so that enterprises can power their AI workloads. It said that it was preparing to deliver the bandwidth required to handle large volumes of data processing, creating what the firm believes is the required high-performance pipeline for AI workloads.
Network giant Cisco has unveiled simplification of its network operations and claims to be in a position to deliver exponential performance with next-generation devices, all while fusing security into the network and making new business workflows possible.
As it announced the platform, the company quoted findings from its IT networking leader survey, which stressed how a major infrastructure shift was underway and that AI could either double the strain or solve it.
Specifically, the research found that 97% of businesses believe they need to upgrade their networks to make AI and IoT initiatives successful. Faced with these challenges, IT teams needed a new approach to scale operations, reduce downtime, and unlock new levels of efficiency and innovation. Cisco warned that there would only be two types of company in the future: those that are really adept with their use of AI, and those that really struggle.
Even though very few businesses around the world are resisting the allure of artificial intelligence (AI), research commissioned by Expereo has revealed a number of major roadblocks to UK AI plans, such as poor infrastructure, resistance from employees, and unreasonable demands, while two-fifths of UK CIOs have warned of unrealistic board expectations of AI.
Despite some of the worrying findings revealed, the research also painted a positive picture for the promise of AI, but only if businesses can overcome existing challenges. Some 88% of UK business leaders surveyed regarded AI as becoming important to fulfilling business priorities in the next 12 months.
