Rising cloud storage fees are putting noticeable pressure on IT budgets and slowing down infrastructure plans for many UK enterprises. According to Wasabi’s 2026 Cloud Storage Index, almost half (48%) of total storage costs now go toward fees rather than actual storage capacity. These fees include things like egress, API calls, and other usage-based charges that sit on top of the basic cost of storing data. This fee-heavy model is leading to frequent budget overruns: - 46% of UK respondents said they exceeded their allocated cloud storage budgets in 2025. - 84% of UK respondents cited at least one fee-related reason for going over budget. The overspend typically comes from a mix of increased storage use, business growth, and migration to the cloud, but fees are becoming a bigger part of the problem each year. As a result, IT leaders are finding it harder to predict costs, which complicates long-term infrastructure planning and can delay or scale back new initiatives.

Cloud storage has become a core building block for AI initiatives, and its cost and performance are directly affecting AI outcomes. Wasabi’s research shows that when organizations were asked about their biggest challenges in implementing AI, the top response was data storage issues—specifically cost, data access, and management. AI models depend on large volumes of high-quality data that must be stored, accessed, and processed efficiently. Some key data points from the study: - Only about one-quarter of respondents have seen a positive ROI from AI so far. - Nearly half (48%) are confident they can achieve positive AI ROI if they improve their infrastructure. - Nearly two-thirds (62%) of budgets are being allocated to data, storage, and compute capacity build-outs over the next year. This shows that organizations are rethinking their AI strategies around infrastructure first. Cost-efficient, reliable storage is essential to keep high-quality data readily available to AI models without creating unsustainable infrastructure costs. In practice, that means IT teams are focusing less on just buying AI software and more on building the right data and storage foundation to support AI at scale.

AI spending patterns are shifting away from a software-first mindset toward a stronger focus on infrastructure, especially storage and compute. Traditionally, most public cloud revenue has come from software and SaaS solutions. However, Wasabi’s findings indicate that AI budgets are now being allocated quite differently: - Only 36% of AI-related spending is going to AI software or SaaS. - The majority of AI budgets are being directed toward infrastructure, with around 62% of budgets earmarked for data, storage, and compute capacity. This represents a change in budget priorities. Organizations are recognizing that to get value from AI, they need to first build a robust infrastructure layer—particularly cloud storage that is predictable in cost and capable of supporting large-scale data workloads. For IT and business leaders, this means cloud strategy is being reenvisioned around: - Managing storage fees more carefully to avoid budget overruns. - Investing in scalable, cost-efficient storage to support AI data growth. - Treating infrastructure as a primary enabler of AI innovation, rather than an afterthought to software purchases. In short, AI is reshaping how organizations think about cloud investments, with infrastructure—and especially storage—moving to the center of budget and planning discussions.