AI pushes storage to the top of IT leaders' agenda

Seagate has released its Data Infrastructure Readiness Report, which examines how businesses are preparing their data infrastructure for wider AI deployment. The study found that 99% of IT leaders expect AI to increase storage requirements.

The findings are based on a survey of 2,712 enterprise technology decision-makers in the United States, China, India, the United Kingdom, Germany, France and Japan. They suggest that companies expanding their use of AI are focusing less narrowly on computing power and more on the condition, accessibility and management of the data that underpins those systems.

Among respondents, 86% said their organisations had already seen moderate or significant return on investment from AI spending. Within that group, one-third reported significant measurable returns, suggesting that many businesses now view AI as a source of commercial value rather than an experimental tool.

That reported value is sharpening attention on the infrastructure needed to support AI at scale. While almost all respondents said AI would drive up storage demand over the next three years, only 38% said their organisations were fully prepared for those long-term data requirements.

Storage focus

The research points to a gap between AI ambition and operational readiness. More than half of respondents, 53%, identified data quality and readiness as a leading obstacle to AI deployment, while 43% cited storage infrastructure challenges.

Those concerns ranked ahead of compute availability, named by 27% of respondents, and energy constraints, cited by 24%. The results indicate that for many organisations, the bottleneck in scaling AI lies less in access to processors and more in how data is stored, governed and prepared for use.

Storage is also moving up the corporate agenda. Seventy-six per cent of respondents said data centre investment ranked among their organisation's top three infrastructure priorities, and 20% said it was their single highest infrastructure investment priority.

The study also found that 98% of respondents believe AI is changing storage from a back-office function into strategic business infrastructure. That shift reflects growing recognition that the quality, availability and retention of data affect how well AI systems perform and how much value organisations can extract from them.

Readiness gap

Businesses surveyed cited a range of barriers to stronger preparedness. The leading issues were AI strategy maturity at 16%, budget and resources at 14%, and data management and governance at 14%.

Those figures suggest the challenge is not simply buying more hardware. Companies appear to be grappling with broader questions of planning, oversight and how data assets are managed over time as AI applications spread across operations.

Melyssa Banda, Senior Vice President of Edge Storage Business at Seagate, said pressure on infrastructure is growing alongside the volume and importance of corporate data.

"AI is reshaping the way organizations plan, build and operate infrastructure," Banda said. "As data volumes grow, so does the value organisations can derive from the data. They need data infrastructure that helps them preserve, access and use more of that data over time. Sustainable Scaling is about making those infrastructure decisions more efficient, more durable and more connected to long-term data value."

Sustainability pressures

The report also highlights the role of energy use and environmental concerns in infrastructure planning. Seventy-seven per cent of organisations said they had delayed or restructured AI infrastructure expansion because of sustainability or energy issues, including 36% that said they had significantly restructured those plans.

Respondents pointed to AI-driven energy consumption and carbon emissions from energy use as their main environmental concerns, at 52% and 51% respectively. At the same time, 97% agreed that extending infrastructure lifecycles significantly improves sustainability, and 94% said they expect their storage operations to become more sustainable over the next five years.

Together, these findings suggest companies are trying to balance AI growth with the costs and practical limits of running larger data estates. Extending the lifespan of existing systems, improving utilisation and reducing the environmental impact of expansion are becoming part of mainstream infrastructure decision-making.

Seagate uses the term "Sustainable Scaling" to describe this approach, arguing that businesses need to increase AI capacity and business value while improving the efficiency of the systems that support data storage and management. The survey findings suggest that, for many companies, this has become an operational necessity rather than a branding exercise.

A further sign of that shift is the extent to which storage is being reclassified internally as a strategic issue. As AI systems move from limited pilots to broader use across departments, companies are having to preserve larger volumes of data, organise it more effectively and keep it accessible for longer periods.

Banda said the next phase of AI deployment will depend on how businesses handle those practical issues.

"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 organisations scale, organize, retain and use the data that AI depends on. The companies that create lasting value from AI will be the ones that treat data infrastructure as a business strategy."