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A CTERA-commissioned study of 16 petabytes of production data reveals most enterprise file storage is dead weight. The company's response: new archiving software paired with AI-driven analytics to shrink primary storage bills.
Enterprises are paying premium prices to store data nobody uses. That is the core finding from research commissioned by cloud file system vendor CTERA, which examined 16 petabytes of live production data across 856 file-share scans in enterprise NAS environments, including regulated industries. The conclusion is stark: only 4.4 percent of stored capacity qualifies as actively used. The rest, 95.6 percent, falls into the category of redundant, obsolete, or trivial data, commonly shortened to ROT.
The granular figures reinforce the scale of the problem. Of total stored capacity, 83.1 percent sits in files untouched for more than a year. Looking at individual files rather than capacity, 97.5 percent had not been modified in over twelve months, and 88 percent had not been accessed in that same window. Perhaps most telling, only 9.9 percent of stored data saw any access at all during a given 90-day period. These are not edge cases. They describe the default state of enterprise file storage.
This matters because the storage tier holding this data is typically the most expensive one in the stack. Primary storage carries premium pricing for performance, redundancy, and availability, none of which idle files actually need. Worse, this dead data still gets backed up, replicated, and protected as if it were mission-critical, multiplying costs across the entire data protection chain.
CTERA CTO Aron Brand framed the issue bluntly. "When only 4.4 percent of capacity is actively used, enterprises are running their most expensive storage tier as what is effectively a cold archive," he said. "That creates a multiplier effect across storage and data protection costs, security exposure, and now the quality of information available to AI systems."
Brand's point about AI systems deserves attention. As enterprises feed internal data into AI tools for search, summarization, and agentic workflows, stale and redundant files degrade the quality of what those systems retrieve and reason over. Cold data is not just an expense problem anymore. It is a data-quality problem for any organization building AI applications on top of its file estate.
CTERA is not simply flagging a problem it profits from solving, though the incentive alignment is obvious. The company has long offered an archival use case that lets authorized users move inactive data from primary storage into cost-efficient archive cloud folders, while keeping that data accessible through CTERA services and metadata.
The newer move is a dedicated Archive function built into Edge Filer v7.13x, which the company says "allows you to archive your inactive data, effectively reducing your storage costs." This is early access build software, version 713.6000.19, and it is not yet generally available. That distinction matters for anyone evaluating the timeline for deployment. Early access typically means limited support, incomplete documentation, and a higher tolerance for bugs among the customers willing to test it.

The archiving function is meant to work alongside CTERA's InsightAI tool, which the company introduced earlier this year as an agentic AI management interface. InsightAI connects data activity, audit trails, metadata, permissions, capacity trends, and security events into a single view, intended to surface where inactive data lives and where action is warranted. The pitch is straightforward: use AI to find the cold data, then use the new Archive function to move it somewhere cheaper.
CTERA is offering flexibility on where InsightAI actually runs. It can be deployed as a CTERA-hosted SaaS product, inside a managed customer VPC on Azure or AWS, or fully within customer-controlled private cloud environments, including AWS GovCloud and Azure Government. That range of deployment options signals CTERA is chasing regulated and security-sensitive customers as much as mainstream enterprise IT buyers. Given that the underlying research explicitly included regulated industries in its sample, this is a deliberate positioning choice rather than an afterthought.
The obvious question is whether "archiving" actually delivers savings proportional to the marketing claims, or whether it simply shifts cost and complexity from one tier to another. Moving 95 percent of an organization's file data somewhere else is not a trivial operation. It requires confidence in access controls, metadata integrity, and retrieval speed when archived files are eventually needed again.
There is also a competitive dimension worth noting. CTERA operates in a market that includes Nasuni and Panzura, both pursuing similar cloud file system strategies. Cold data management is becoming a standard feature expectation rather than a differentiator, which puts pressure on CTERA to prove its Archive function and InsightAI combination actually outperforms rivals on cost reduction and ease of use, not just on paper.
Enterprises should also treat the underlying Cold Data Report with appropriate skepticism regarding sample selection. Vendor-commissioned research examining a vendor's own customer base, even at 16 petabytes across 856 scans, is not the same as an independent industry-wide audit. The numbers are directionally credible given how consistently they align with broader industry data lifecycle patterns, but they should inform decision-making rather than substitute for an organization's own data audit.
The 95.6 percent inactive data figure is a useful wake-up call for any IT budget owner still paying premium rates for stale files. Whether CTERA's Archive function delivers the promised savings will depend on real-world deployment outcomes once the early access label comes off. Enterprises evaluating this space should benchmark actual cost reduction and retrieval performance against claims, and weigh CTERA's offering against comparable tools from Nasuni and Panzura before committing budget.
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CTERA finds 95% of enterprise file data rarely used
↗ https://www.theregister.com/file/2026/09/15/ctera-finds-95-of-enterprise-file-data-rarely-used/5296552
About the author
Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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