AI Storage Demand Is Rising Faster Than Enterprise Readiness, Seagate Study Finds
A Seagate-backed survey found 99% of IT leaders expect AI to raise storage needs, while only 38% say their organizations are fully prepared.
Enterprise AI projects are turning storage from a back-office capacity issue into a strategic infrastructure test, Frontier Enterprise reported from a Seagate Technology study that found almost every surveyed IT leader expects AI to lift storage demand while far fewer feel ready for the increase.
The study, conducted for Seagate by Recon Analytics between May and June 2026, questioned 2,712 enterprise technology decision-makers across seven markets: the US, China, India, the UK, Germany, France and Japan.
Its central gap is stark: 99% of IT leaders at organizations expect AI workloads to push storage needs higher, while preparedness lags at 38%.
The readiness shortfall comes even as AI spending is already producing measurable returns for many companies.
Nearly nine in 10 organizations, or 86%, reported moderate or significant ROI from AI investments.
One-third, 33%, said those returns were significant and measurable, which suggests the storage question is emerging after pilots have begun to prove their business case rather than before adoption starts.
Demand expectations are not modest.
Over the next three years, 99% of organizations expect AI to increase storage requirements, and 32% expect the increase to exceed half of current needs.
That forecast makes storage planning a scaling issue for enterprises that want to move from isolated AI use cases to broader deployment across products, operations and customer-facing workflows.
The obstacles identified in the research put data foundations ahead of some more visible constraints.
Data quality and readiness ranked as the leading AI deployment challenge at 53%, followed by storage infrastructure at 43%.
Both stood ahead of compute availability at 27% and energy constraints at 24%, showing that organizations see the condition, movement and retention of data as a practical limiter on AI expansion.
Storage is also moving higher in capital planning.
More than three-quarters of organizations, 76%, ranked data centre investment among their top three infrastructure priorities.
One in five, or 20%, now considers it the single highest infrastructure investment priority.
The same survey points to why preparedness remains uneven.
AI strategy maturity was the most cited barrier to greater readiness at 16%, while budget and resources accounted for 14% and data management and governance for another 14%.
Those figures indicate that the gap is not only about buying more storage hardware; it also reflects decisions about what data to keep, how to organize it and how to make it usable over time.
Nearly all respondents, 98%, agreed that AI is transforming storage into strategic business infrastructure.
Seagate framed the finding as evidence that data is becoming a long-term asset that companies must preserve and manage if AI systems are to keep generating value after initial deployment.
Melyssa Banda, Seagate Technology’s senior vice president of edge storage business, said organizations need infrastructure that lets them preserve, access and use more data as volumes grow.
“The next phase of AI will require capacity growth, but capacity alone will not be enough,” Banda said.
Her conclusion links the storage buildout to operating discipline rather than raw expansion.
Banda added that lasting AI value will depend on companies treating data infrastructure as part of business strategy.
