Businesses See AI ROI But 62% Can't Handle Surging Storage Demands Driven By AI

Enterprise AI Adoption Delivers Returns But Exposes Infrastructure Gaps

Artificial intelligence is delivering measurable returns on AI investments for businesses worldwide, yet a critical infrastructure crisis looms. Seagate Technology's 2026 Data Infrastructure Readiness Report reveals that 86% of organizations report moderate or significant AI ROI, with one-third seeing substantial measurable financial or operational benefits1

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. Despite this success, only 38% of organizations consider themselves prepared to meet AI's growing data demands—less than four out of ten companies are ready for what's coming1

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The study surveyed 2,712 enterprise technology decision-makers across the US, China, India, the UK, Germany, France, and Japan during May and June 2026. The findings expose a widening gap between the pace of enterprise AI adoption and the underlying data infrastructure readiness required to sustain it1

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. While recent years saw AI conversations center stubbornly on computing power, organizations now face mounting challenges in how data sourced from AI is accessed, stored, retained, and managed.

Storage Infrastructure Emerges as Primary Obstacle to AI Deployment

Storage demands have become the second-most significant barrier to AI deployment. According to the report, 43% of respondents identify storage infrastructure as an obstacle to AI deployment, ranking just behind data quality and readiness, which 53% cite as their primary challenge1

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. These two roadblocks dwarf other concerns like compute availability at 27% and energy constraints at 24%1

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The numbers paint a stark picture: 99% of IT leaders expect AI workloads to increase storage requirements over the next three years1

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. Nearly seven in ten respondents expect storage requirements to increase by at least 26%, while 32% anticipate surging storage demands driven by AI will push growth beyond 50%1

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AI Transforms Storage Into Strategic Business Asset

As AI adoption accelerates, data supporting these systems is becoming a longer-term business asset. Nearly every respondent—98%—agreed that AI is transforming storage from a seemingly basic component into a strategic element of business infrastructure1

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. This shift reflects how training material, active datasets, model checkpoints, and retained outputs impose substantially different infrastructure requirements throughout an AI system's lifecycle2

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Investments in data centers are climbing organization priority lists in response. Just over three out of four organizations—76%—ranked data centers among their top three infrastructure investment priorities, with one out of five identifying it as their single highest priority1

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. However, immature AI strategies, limited budgets and resources, and data management and governance challenges remain significant barriers to organizational preparedness1

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Sustainability Concerns Reshape Infrastructure Expansion Plans

Sustainability and energy consumption are influencing how organizations shape and expand their AI infrastructure. A striking 77% of surveyed organizations reported delaying or restructuring AI infrastructure expansion due to sustainability or energy concerns, with 36% admitting they had significantly revised expansion plans1

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Power consumption emerged as the most frequently considered environmental factor for storage hardware, cited by 62% of respondents2

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. AI-associated energy consumption topped environmental concerns at 52%, followed closely by carbon emissions and energy use at 51%1

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. Equipment lifespan followed at 55%, with respondents broadly connecting longer hardware service periods with improved sustainability across data center operations2

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Current confidence in sustainable operations remains modest, with only 39% describing their storage operations as highly sustainable under present conditions. However, that proportion rises to 61% when respondents assess where their organizations expect storage sustainability to stand five years from now2

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. Funding levels influence these expectations significantly: 70% of organizations with sustainability budgets above $100 million expect highly sustainable operations within five years, compared to just 48% of organizations with annual sustainability budgets below $1 million2

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For organizations expanding AI operations, capacity planning, storage architecture, equipment lifespan, and energy consumption are becoming increasingly interconnected decisions that demand immediate attention2

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