Storage teams are enduring the bulk of AI-fueled SSD and memory price inflation, pushing teams to consolidate storage tiers and address a critical pain point: large portions of enterprise data have fallen outside effective internal governance and control.
An Omdia research report commissioned by Verge.io, released this week, lays out the full scope of challenges facing storage professionals. The study confirms DRAM prices nearly doubled in a single quarter, while SSD costs rose by over 50% over the same period.
As market conditions stand, all current data resides on hardware procured at elevated 2026 price points. A persistent unresolved gap remains between the storage capacity enterprises purchase and the actual workload demands they need to support.
The report also highlights a restrained supply-side stance: hardware vendors are opting not to expand production to ease market tightness, and industry forecasters do not anticipate a return to 2025-level pricing in the near term.
This paradigm shift is forcing IT and storage leaders to reshape operational strategies, prioritizing software-centric solutions over increasingly costly and scarce hardware infrastructure.
Research data shows merely 2% of surveyed enterprises have no plans to consolidate storage infrastructure or are not already executing consolidation initiatives. Driven by infrastructure demand from hyperscalers and AI model developers that fuels ongoing price hikes, nearly 75% of businesses are slowing their on-premises AI deployment progress amid persistent supply shortages and cost pressures.
Enterprise on-premises data volumes continue expanding rapidly across the industry. Twenty-seven percent of organizations manage 1PB to 10PB of internal data, with an equal share handling 11PB to 25PB, and 18% maintaining 25PB to 50PB. At the high end, 6% of enterprises oversee 100PB or more of on-prem data. Additionally, data growth remains robust, with nearly three-quarters of respondents reporting annual data volume increases ranging from 11% to 50%.
Faced with capacity shortfalls and cost spikes, enterprises are turning to infrastructure consolidation, software-defined architectures and cloud adoption to bridge resource gaps. The cloud stands as a primary mitigation route: nearly half of businesses not yet leveraging cloud storage are planning moderate cloud investment, while 31% intend to pursue substantial cloud spending.
Omdia chief analyst Simon Robinson noted unexpected industry momentum behind one key solution: “We were surprised by how many organizations are evaluating software-defined storage as a viable remedy for current market challenges.”
Verge.io CMO George Crump elaborated on the trend: “Buyers are spontaneously prioritizing software-defined storage above other options. Our analysis indicates enterprises favor this approach because hardware-agnostic software architectures offer long-term stability amid ongoing hardware supply and pricing volatility.”
Crump reiterated the core industry dilemma: “Every byte of current enterprise data sits on hardware purchased at 2026’s inflated price points. The fundamental mismatch between purchased capacity and real-world workload requirements still has no industry-wide fix.”
Against this backdrop, enterprises must refine core operational practices, including storage array allocation, performance optimization, and rationalization of redundant infrastructure architectures.
Key actionable optimizations include streamlining disparate architecture stacks, tiering cold data to lower-cost media, and eliminating redundant backup hardware systems. These are standard best practices, yet most enterprises have never measured or benchmarked these operational inefficiencies. The incentive is clear: 30TB SSD pricing now sits at 22.6 times equivalent disk storage costs, a drastic jump from the 4.9x premium seen previously.
A major barrier hindering optimization is poor enterprise data visibility. More than one-third of companies report 50% to 75% of their data is dark and unclassified, while an additional 13% state dark data accounts for 76% to 90% of their total storage volume.
This massive pool of unstructured, ungoverned dark data creates a dual dilemma: it could serve as valuable training resources for enterprise AI projects, yet it also represents a continuous financial burden that drains already constrained storage budgets.
Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
WhatsApp / WeChat: +86 13426366826
Email: yangyd@qianxingdata.com
Website: www.qianxingdata.com/www.storagesserver.com
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