Andriy Onufriyenko/Getty ImagesZDNET’s key takeaways
- A brand new examine finds 62% of organizations are ill-prepared to deal with surging storage wants.
- Organizations should lean in to AI’s rising knowledge calls for and infrastructure readiness.
- “Sustainable scaling” often is the key to optimizing AI development, in keeping with Seagate’s examine.
Synthetic intelligence is forcing organizations to judge will increase in knowledge storage like by no means earlier than, however lower than 40% of companies imagine their infrastructure is provided to deal with the growth, in keeping with new analysis from Seagate Expertise.
Seagate Expertise’s 2026 Data Infrastructure Readiness Report discovered that 99% of IT leaders anticipate AI to extend their group’s storage wants over the following three years. In actual fact, 32% anticipate their storage demand will develop by greater than 50% on account of AI.
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Regardless of this, solely 38% of organizations say they’re ready to satisfy AI’s rising knowledge calls for. That’s lower than 4 out of ten.
Seagate’s findings, published on September 14, are based mostly on a survey of two,712 enterprise know-how decision-makers throughout the US, China, India, the UK, Germany, France, and Japan. Recon Analytics performed the analysis on behalf of Seagate throughout Might and June 2026. The survey aimed to look at respondents’ views on their organizations’ AI readiness, infrastructure funding, storage structure, infrastructure effectivity, sustainability, and long-term infrastructure planning.
The report’s knowledge suggests a widening hole between the tempo of enterprise AI adoption and the underlying knowledge infrastructure (i.e., storage) wanted to assist it. In recent times, the AI dialog has stubbornly centered on computing energy. Now, companies and organizations throughout the globe are more and more encountering challenges in how knowledge sourced from AI is accessed, saved, retained, and commanded.
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Probably the most generally reported problem to deploying AI amongst respondents is knowledge high quality and readiness, cited by 53% of respondents. The runner-up is storage infrastructure, cited by 43% of respondents. These two roadblocks are reported at considerably greater charges than others, similar to compute availability (27%) and vitality constraints (24%).
AI will increase the worth of information, nevertheless it wants someplace to go
The elevated push for extra sturdy infrastructure arrives as some companies receive measurable returns from AI. Seagate’s report particulars that 86% of organizations are seeing “reasonable or important” returns on their AI investments, with one-third reporting “important measurable” returns.
As AI creeps into extra enterprise operations and setups, the info supporting these methods is turning into a longer-term enterprise asset, and the business is aware of it. Practically each respondent of Seagate’s survey (98%) agreed that AI is remodeling the seemingly fundamental part of storage right into a strategic aspect of enterprise infrastructure.
And with extra storage comes the necessity for extra locations to accommodate it. In response to Seagate’s findings, investments in knowledge facilities are shifting greater on group precedence lists. Simply over three out of 4 organizations (76%) ranked knowledge facilities amongst their prime three infrastructure funding priorities, with one out of 5 even figuring out it as their single highest precedence.
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The info middle debate is getting lots of consideration, with fights towards knowledge facilities popping up around the country. Regardless, the business’s push for extra funding into storage will seemingly proceed, although it’s not the one issue stopping companies from feeling absolutely ready.
Immature AI methods, restricted budgets and assets, and knowledge administration and governance challenges have been additionally recognized by survey respondents as important boundaries to their group’s preparedness.
‘Sustainable scaling’
Whereas knowledge facilities and different types of AI infrastructure have ruffled the feathers of many cities, cities, states, and people, Seagate’s report signifies that sustainability and vitality are influencing how organizations form, plan, and develop their AI infrastructure.
Of organizations surveyed, 77% stated they’d delayed or restructured AI infrastructure growth as a result of sustainability or vitality issues, with 36% admitting they’d considerably revised growth plans because of this.
AI-associated vitality consumption was the highest environmental concern, with 52% of respondents indicating so, adopted by carbon emissions and vitality use at 51%.
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Ninety-seven % of respondents additionally agreed that extending the usable lifecycle of infrastructure can enhance sustainability, and 94% anticipated their storage operations turning into extra sustainable inside the subsequent 5 years.
Seagate defines this vital want for continued funding in knowledge technique, authorities, and AI infrastructure as a brand new crucial, which thre firm calls sustainable scaling.
“Sustainable scaling is the flexibility to extend AI capability and enterprise worth whereas constantly enhancing the efficiencies of the infrastructure that helps it,” in keeping with the report. “As policymakers, regulators and the general public place extra scrutiny on the expansion of AI infrastructure, sustainable scaling will play a vital function within the long-term viability of a sturdy and wholesome AI financial system.”
The underside line
Seagate anticipates that the following part of AI will create extra knowledge, however capability alone won’t decide which organizations succeed. The report concludes that the defining issue will likely be every group’s “skill to maintain knowledge accessible and prepared to be used whereas effectively managing the infrastructure calls for that include development.”
And whereas this work might already be underway for 38% of organizations, for many, the hole between being largely ready and absolutely ready stays broad.
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Seagate’s report signifies that closing this hole requires an infrastructure technique constructed across the “full knowledge lifecycle.”
“Organizations want to grasp what knowledge they’ll create, how shortly totally different workloads have to entry it, how lengthy it could retain worth and which operational measures will information development. These choices present the muse for sustainable scaling and for lasting worth from AI.”
