By James Hernon | 8 April 2026
Across the technology industry, organisations have already started to feel the impact of a global memory shortage. The demand for AI systems has risen sharply, and the memory needed to support them now takes up a significant share of global production. As a result, pressure has increased on the traditional DRAM and NAND used across servers, storage, networking equipment and end user devices.
Analysts are clear that this is not a short-term issue. Most forecasts suggest that supply constraints and higher pricing are likely to continue all the way through to 2027. If your organisation is planning infrastructure upgrades or network transformation projects, then building in more lead time is now more important than ever.
AI systems have quickly become the biggest consumers of memory worldwide. We are now seeing AI data centres use around 70 percent of all memory chips produced, leaving a much smaller share available for everything else, from enterprise servers and networking to end user devices.
To meet this surge in demand, manufacturers have shifted their focus towards high bandwidth memory and other AI-focused components. This change is not about increasing overall supply, but about redirecting where existing production capacity is used. That shift has reduced the amount of capacity available for traditional DRAM, which is still relied on across enterprise servers, laptops and network infrastructure. Industry experts describe this as a structural realignment rather than a temporary imbalance.
In practical terms, that means pressure on general-purpose memory is likely to continue until new capacity becomes available.
Tightening supply is now feeding directly into higher memory pricing across the market. General memory prices rose by more than 50 percent in the first quarter of 2026, with DRAM pricing in many areas now roughly double what it was in early 2025. In response, PC manufacturers are already forecasting price increases of between 15 and 20 percent across the second half of the year as they manage higher component costs.
These pricing pressures extend beyond end user devices and are increasingly visible across servers, storage and networking hardware. AI servers require significantly more memory per system than traditional enterprise environments, which continues to absorb available supply and reduce availability elsewhere. For businesses, this often results in shorter quote validity, more frequent pricing changes and less certainty as vendors respond to ongoing volatility.
Networking infrastructure is increasingly exposed
Modern networking platforms place far greater demands on memory than previous generations of hardware. Capabilities such as deeper packet inspection, integrated security, traffic optimisation and real-time analytics are now built into a single platform, rather than spread across multiple devices. This is particularly evident in SD‑WAN, where one appliance is expected to handle far more work at the network edge.
As memory-intensive platforms become the norm, networking equipment is more exposed to ongoing supply constraints. IT leaders planning SD-WAN migrations or refreshing core network infrastructure may encounter longer lead times, fewer configuration options and tighter availability. Building extra time into network projects and making procurement decisions earlier than usual can help reduce disruption.
User device refresh cycles will still feel the impact
End user devices are not under the same level of pressure as servers or networking hardware, but they are not immune. Memory remains a meaningful part of the overall cost of PCs and smartphones, and analysts expect prices in these categories to rise by between three and eight percent, depending on how supply develops.
For many organisations, operating system deadlines are no longer the primary driver of refresh cycles. However, higher costs, limited configurations and longer lead times may still affect rollout plans. At the same time, the rapid introduction of AI features in Windows 11 and modern mobile devices is increasing baseline memory requirements. This makes it sensible to review endpoint strategies based on performance needs and suitability, rather than fixed replacement schedules.
Supply constraints may impact server and network upgrades
AI servers require significantly more memory per system than traditional enterprise workloads. As a result, a large proportion of global production continues to be reserved for AI infrastructure, reducing availability across servers, storage and networking equipment. Periods of constrained supply are likely to persist throughout 2026.
For IT leaders planning infrastructure upgrades, this may translate into longer lead times, more frequent pricing changes and closer scrutiny of memory-heavy configurations. Projects that rely on specific hardware profiles may need additional flexibility, either in timing or specification, to stay on track as market conditions continue to shift.
1. Plan earlier and maintain flexibility in build specifications
With supply expected to remain tight until 2027, the most effective strategy your organisation can adopt is to allow more lead time for hardware purchases. Organisations that plan earlier tend to have more options when it comes to securing allocation, managing cost and avoiding last‑minute changes that can disrupt delivery timelines.
Flexibility also plays a bigger role than it used to. Small adjustments to memory capacity, storage configurations, product families or even vendor choice can help reduce exposure to allocation issues during periods of high demand. Building this flexibility into specifications from the outset makes it easier to respond when availability changes.
2. Reassess infrastructure roadmaps and prioritise critical network upgrades
Given the increasing memory requirements of modern networking platforms, particularly SD-WAN, IT leaders should take time to review their broader infrastructure roadmap. Projects involving WAN edge consolidation, branch connectivity upgrades or the adoption of new SD-WAN platforms may require adjusted timelines to account for supply constraints and pricing volatility.
Focusing on business-critical network components first, and sequencing remaining upgrades to match market availability, can help maintain resilience while controlling cost pressures.
3. Work closely with partners who monitor market conditions
Vendors continue to adjust pricing policies, quote validity windows and order processes in response to ongoing memory volatility. These changes can happen quickly and are not always visible until late in the procurement process.
Working with a partner that actively monitors market conditions helps organisations stay informed and avoid unwanted surprises. Here at Bistech, we track vendor updates and supply trends in real time, allowing us to guide customers through procurement challenges, highlight potential risks early and identify the most resilient options for their requirements.
The global memory shortage is directly affecting servers, storage and increasingly the networking infrastructure that underpins modern enterprise environments. AI demand is consuming the majority of global memory production, which is tightening supply and driving higher prices for traditional DRAM and NAND. Analysts expect these conditions to continue into 2027.
Now is the right time for organisations to reassess upcoming network and infrastructure plans, build more lead time into procurement and ensure strategies are prepared for ongoing volatility. If you would like tailored guidance or want to discuss your requirements, our experts are ready to help you explore the most effective path forward.
Book a call with our team today to stay ahead of the disruption and keep your technology roadmap on track.
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