AI ROI rises but storage infrastructure lags behind
Only 38% of businesses feel prepared for AI's growing data demands
1Storage unpreparedness crisis
Seagate's 2026 survey of 2,712 tech decision-makers across seven countries reveals only 38% of organizations feel prepared for AI's storage demands. 99% expect increased storage needs from AI, with 32% anticipating over 50% growth. The research conducted by Recon Analytics highlights a critical infrastructure gap emerging as AI adoption accelerates globally, shifting focus from computing power to data management challenges.
2Top AI deployment barriers
Data quality issues (53%) and inadequate storage infrastructure (43%) emerge as primary obstacles to AI implementation, surpassing compute availability (27%) and energy constraints (24%). These findings from Seagate's September 2026 report demonstrate how storage has become a strategic bottleneck, with 98% of respondents agreeing AI transforms storage into critical business infrastructure. The survey covered enterprises in US, China, India, UK, Germany, France and Japan.
3ROI versus readiness paradox
While 86% of organizations report moderate or significant returns from AI investments (33% seeing substantial ROI), most struggle with infrastructure. 76% prioritize data center investments, with 20% making it their top priority. This contradiction shows businesses are achieving AI value despite foundational gaps. The report suggests this imbalance may become unsustainable as AI-generated data volumes grow exponentially in coming years.
4Sustainability reshaping expansion
77% of organizations delayed or restructured AI infrastructure plans due to sustainability concerns, with 36% making significant revisions. Energy consumption (52%) and carbon emissions (51%) dominate environmental worries. Notably, 97% believe extending infrastructure lifecycle improves sustainability, while 94% expect greener storage operations within five years. These constraints are forcing new approaches to data center growth and management.
5The sustainable scaling imperative
Seagate introduces 'sustainable scaling' as the new industry imperative - increasing AI capacity while improving infrastructure efficiency. As public scrutiny grows, this approach becomes vital for long-term AI economy viability. The concept requires balancing data creation, access speed, retention value and operational measures. The report warns capacity alone won't determine success, but rather data availability and efficient infrastructure management.
6Data lifecycle strategy gap
Only 38% of organizations have begun addressing the full data lifecycle needs for AI. The majority lack strategies for data creation patterns, access requirements, value retention periods and growth metrics. Seagate emphasizes these decisions form the foundation for sustainable AI scaling. Without comprehensive lifecycle planning, businesses risk accumulating technical debt as AI data volumes multiply.
7Global infrastructure priorities
The survey reveals regional variations in AI infrastructure challenges. While storage limitations affect all markets, developing economies face additional constraints in energy availability and compute resources. Mature markets grapple more with sustainability regulations and community opposition to data center expansion. These differences require tailored approaches to AI infrastructure investment and management.
8The next phase of AI scaling
As AI moves beyond initial implementation, the focus shifts to operational sustainability. Success will depend on organizations' ability to maintain data accessibility while managing growing infrastructure demands. The report concludes that businesses achieving this balance will gain long-term competitive advantage, while those failing to address storage challenges risk being overwhelmed by their own AI-generated data volumes.
Original article: Latest news — AI ROI rises but storage infrastructure lags behind