As AI moves from early use cases into broader deployment, data infrastructure is becoming more central to how organizations store, access, manage and use data at scale.
This is according to a report from Seagate Technology, which is based on research conducted by Recon Analytics between May and June 2026.
On behalf of Seagate, Recon Analytics surveyed 2,712 enterprise technology decision-makers across the United States, China, India, the United Kingdom, Germany, France and Japan.
Results show that nearly all (99%) organizational IT leaders expect AI to increase storage requirements, but only 38% believe they are fully prepared to meet that demand.
Nearly nine in 10 organizations (86%) report moderate or significant ROI from AI investments, including one-third (33%) reporting significant measurable ROI.
Also, nearly every organization (99%) expects AI to increase storage requirements over the next three years, with nearly one-third (32%) expecting storage needs to increase by more than half.
Data quality and readiness (53%) and storage infrastructure (43%) rank as the leading challenges to deploying AI, with storage infrastructure ranking ahead of compute availability (27%) and energy constraints (24%).
Further, nearly all organizations (98%) agree that AI is transforming storage into strategic business infrastructure.
“As data volumes grow, so does the value organizations can derive from the data,” said Melyssa Banda, SVP of Edge Storage Business at Seagate Technology. “They need data infrastructure that helps them preserve, access and use more of that data over time.”
Findings also show that nearly all organizations (98%) agree that AI is transforming storage into strategic business infrastructure.
Also, nearly all organizations (99%) expect AI to increase storage requirements over the next three years, yet only 38% of organizations say they are fully prepared for AI’s long-term data demands.
Seagate Technology said the findings suggest data is becoming more than an input; it is a long-term asset that organizations need to preserve, manage and use effectively to create business value over time.
As AI increases storage requirements, preparing data infrastructure to support AI at scale requires more than adding capacity, yet only 38% of organizations say they are fully prepared for AI’s long-term data demands.
The research shows organizations are assessing data readiness, storage infrastructure, governance, budget and AI strategy maturity as they move toward broader AI deployment.
Only 38% of organizations say they are fully prepared for AI’s long-term data demands.
More than three-quarters of organizations (76%) rank data center investment among their organization’s top three infrastructure priorities, while one in five (20%) now consider it their single highest infrastructure investment priority.
AI strategy maturity (16%), budget and resources (14%), and data management and governance (14%) are the leading barriers to greater preparedness.
Data quality and readiness (53%) and storage infrastructure (43%) rank as the leading challenges to deploying AI, with storage infrastructure ranking ahead of both compute availability (27%) and energy constraints (24%).
Seagate Technology said these findings point to a broader shift in enterprise AI planning. Organizations are not only asking how to deploy AI, but how to build the data foundation needed to make AI useful, scalable and valuable over time.
“The next phase of AI will require capacity growth, but capacity alone will not be enough,” Banda said.
“It will be defined by smarter infrastructure decisions on how effectively organizations scale, organize, retain and use the data that AI depends on,” Banda added. “The companies that create lasting value from AI will be the ones that treat data infrastructure as a business strategy.”
