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aiqbench analysis

This report highlights a critical bottleneck in enterprise AI adoption: while nearly all IT leaders anticipate surging storage demands from generative models, less than 40% feel their current infrastructure can support the necessary scale. The data reveals that the industry's focus has shifted from merely acquiring compute power to addressing the foundational challenges of data quality, retention strategies, and sustainable storage architecture. Without resolving this readiness gap, organizations risk stalling AI growth despite having the algorithms and models in place.
Sources coveringZDNet, techradar.com, AWS, Fortune
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Businesses finally seeing AI ROI, but 62% can’t handle the storage demands

ZDNet5 min read

A Seagate study finds that 99% of IT leaders expect AI to drive increased data storage needs, but only 38% are prepared to meet them, revealing a significant readiness gap.

A new study finds 62% of organizations are ill-prepared to tackle surging storage needs. Organizations must lean in to AI’s growing data demands and infrastructure readiness. “Sustainable scaling” may be the key to optimizing AI growth, according to Seagate’s study. Artificial intelligence is forcing organizations to evaluate increases in data storage like never before, but less than 40% of businesses believe their infrastructure is equipped to handle the expansion, according to new research from Seagate Technology. Seagate Technology’s 2026 Data Infrastructure Readiness Report found that 99% of IT leaders expect AI to increase their organization’s…

Excerpt shown under the publisher's RSS terms · 95 words · full text and figures are on the publisher's site

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