62% of Enterprises Can't Meet AI's Storage Demands, Seagate Finds

Only 38% of organizations say their infrastructure can handle the storage expansion AI demands, even though 99% of IT leaders expect AI to increase their storage needs over the next three years. That finding anchors Seagate Technology's 2026 Data Infrastructure Readiness Report, published September 14, and it exposes a widening gap between the pace of enterprise AI adoption and the data infrastructure underneath it.

The stakes are concrete. Some 32% of the surveyed decision-makers anticipate their storage demand will grow by more than 50% as a result of AI. Yet fewer than four in ten organizations consider themselves prepared to meet that growth.

Recon Analytics conducted the research on behalf of Seagate during May and June 2026, surveying 2,712 enterprise technology decision-makers across the US, China, India, the UK, Germany, France, and Japan. The survey covered AI readiness, infrastructure investment, storage architecture, infrastructure efficiency, sustainability, and long-term planning.

Storage is now the blocker, not compute

For years, the AI conversation centered on computing power. Seagate's data suggests the bottleneck is shifting. The most commonly reported challenge to deploying AI is data quality and readiness, cited by 53% of respondents. Storage infrastructure follows at 43%. Both dwarf compute availability (27%) and energy constraints (24%).

The pressure arrives as businesses finally see measurable returns. Seagate's report finds 86% of organizations are seeing "moderate or significant" returns on their AI investments, and one-third report "significant measurable" returns. As AI spreads into more business operations, the data feeding those systems becomes a longer-term business asset. Nearly every respondent — 98% — agreed that AI is transforming storage from a basic component into a strategic element of business infrastructure.

That shift is showing up in budgets. Just over three in four organizations (76%) ranked data centers among their top three infrastructure investment priorities, and one in five called data centers their single highest priority. The investment push continues despite public pushback, with fights against data center construction cropping up across the US.

Sustainability is reshaping expansion plans

Energy and sustainability concerns are already altering how organizations build. Seagate found that 77% of organizations have delayed or restructured AI infrastructure expansion due to sustainability or energy concerns, and 36% admitted they had significantly revised expansion plans as a result. AI-associated energy consumption ranked as the top environmental concern at 52%, followed by carbon emissions and energy use at 51%.

Ninety-seven percent of respondents agreed that extending the usable lifecycle of infrastructure can improve sustainability, and 94% expect their storage operations to become more sustainable within the next five years.

Seagate frames the required investment in data strategy, governance, and AI infrastructure as a new imperative it calls sustainable scaling. "Sustainable scaling is the ability to increase AI capacity and business value while continuously improving the efficiencies of the infrastructure that supports it," the report states. "As policymakers, regulators and the public place more scrutiny on the growth of AI infrastructure, sustainable scaling will play a critical role in the long-term viability of a robust and healthy AI economy."

Capacity won't decide the winners

Seagate anticipates the next phase of AI will create more data, but the report concludes that raw capacity will not determine which organizations succeed. The defining factor will be each organization's "ability to keep data available and ready for use while efficiently managing the infrastructure demands that come with growth."

Closing the readiness gap, the report argues, requires an infrastructure strategy built around the "full data lifecycle." As the report puts it: "Organizations need to understand what data they will create, how quickly different workloads need to access it, how long it may retain value and which operational measures will guide growth. Those decisions provide the foundation for sustainable scaling and for lasting value from AI."

For the 38% already prepared, that work is underway. For everyone else — the 62% who told Seagate they cannot yet handle AI's storage demands — the gap between mostly prepared and fully prepared remains wide, and the next three years of storage growth will test whether they can close it.