By Sally Kimeu, Territory Sales Manager for East Africa at Nutanix
Imagine an enterprise IT team approving a storage refresh based on a hardware quote that made sense at the start of the budget cycle. By the time approvals, procurement, import timelines and negotiations are complete, the components behind that decision may have increased sharply in price. The quote was not necessarily wrong. The market simply moved faster than the procurement cycle.
That scenario is becoming increasingly familiar across enterprise IT. It is forcing organisations to rethink more than just how they buy storage hardware. Storage planning now has to account for component price volatility, AI-driven demand, supply constraints and local budget pressures.
The market data illustrates the scale of the challenge. NAND flash prices have risen 246% since the start of 2025. According to semiconductor research firm TrendForce, enterprise SSD contract prices are forecast to increase a further 53–58% in a single quarter. Server DRAM is not far behind, with prices projected to surge more than 60% quarter-on-quarter in early 2026. These are not the conditions under which any organisation should make long-term bets on proprietary storage hardware.
For organisations across Africa, those global movements are amplified by exchange-rate volatility, imported hardware costs, extended procurement cycles and, in many markets, limited local manufacturing capacity. The challenge is that component markets are moving faster than enterprise planning and procurement processes can adapt.
Across the continent, organisations are also balancing continued investment in on-premises infrastructure with growing cloud adoption. Hybrid IT has become the operating model for many enterprises, making storage decisions more strategic than ever. Infrastructure needs to support today’s operational requirements while remaining flexible enough to accommodate future growth, AI workloads and evolving business priorities without forcing costly refresh cycles.
That gap is unlikely to close any time soon, and organisations that have not rethought how they buy and manage storage are increasingly paying the price.
The hidden cost of staying still
Proprietary storage architectures concentrate value in the hardware itself. Features, performance improvements and scalability are tied to appliance generations, which means the vendor controls both the product roadmap and, effectively, the refresh timeline. In stable markets, this is simply an accepted limitation. In today’s environment, it has become a significant financial risk.
Across much of Africa, enterprise hardware and support contracts remain heavily exposed to imported costs and foreign exchange movements. That model becomes increasingly difficult to sustain when IT budgets are already under pressure.
The acquisition cost of storage is only part of the picture. Support renewals on ageing hardware routinely outpace inflation, and organisations can find themselves paying premium maintenance rates on systems whose remaining business value no longer justifies the expense.
Operational complexity adds another layer of cost. Running separate silos for block, file and object storage increases management overhead, while the true cost of the traditional model becomes harder to defend than the original capital investment suggested.
Siloed architectures also create inefficiencies that compound over time. Capacity can sit stranded in one environment while another runs short, a problem that becomes more costly as workloads diversify. Organisations supporting AI-driven pipelines alongside conventional enterprise applications are finding that infrastructure designed for a simpler era does not bend easily under the new load.
Separating the intelligence from the iron
The case for software-defined storage has become as much a business decision as a technology one. When storage services are handled in software rather than locked into a specific appliance, organisations have more flexibility over when, how and where they refresh infrastructure.
Physical infrastructure still matters. Modern platforms can take full advantage of NVMe, high-speed networking and newer server architectures. The difference is that the value resides in the storage layer and operating model rather than in a single appliance. That matters when hardware pricing is unpredictable and procurement teams need more options, not fewer.
Many organisations cannot afford to rip and replace infrastructure every few years, especially when lead times and costs are harder to predict. A software-defined approach allows older and newer hardware to operate under a single management model, making it possible to refresh infrastructure in stages and extend the useful life of existing assets. This gives IT teams greater flexibility while reducing unnecessary disruption during infrastructure renewal cycles.
Security and AI have raised the stakes
Cost pressure is only part of the story. Storage now sits much closer to the centre of business resilience. Ransomware recovery, auditability, data protection and compliance all depend on what happens at the infrastructure layer. Capabilities such as immutable snapshots, controlled recovery and policy-based access are becoming part of how organisations demonstrate they can protect and restore critical data.
This is especially relevant for organisations across sectors such as financial services, telecommunications, retail, healthcare, mining and government, where data growth, cyber resilience and service availability are already closely linked to operational and business risk.
The second is AI. The volume of unstructured data that AI pipelines generate and consume is growing at a rate that challenges fixed-capacity architectures, and the performance consistency that model training and inference demand is unforgiving of infrastructure bottlenecks. Organisations building AI capability on storage infrastructure that cannot scale or adapt quickly enough are discovering that infrastructure limitations carry commercial consequences. Slow data access, stranded capacity and rigid refresh cycles can all affect how quickly AI use cases move from experiment to production.
The storage decision has changed
The storage conversation has moved on. Most enterprise IT teams already understand that software-defined storage is mature enough for serious workloads. The harder question is whether it still makes sense to base long-term storage strategy on hardware cycles that the organisation cannot control, especially when component pricing, supply availability and data demands are shifting so quickly.
Software-defined storage does not eliminate hardware costs. It changes how exposed the organisation is to hardware volatility as a strategic risk. When storage value resides in software, refresh decisions can be made with more control over timing, vendor choice, lifecycle and cost. In today’s environment, that flexibility and control are becoming the strongest economic arguments for software-defined storage.