New Iron Mountain research finds that while 95% of organisations call using data to improve business outcomes a top priority, 86% have had AI projects delayed or cancelled because of data concerns in the past 12 months. The findings come from the company's report The Information Supercycle, released at Gartner IT Symposium in Orlando on 19 October 2026.
Data preparation is eating project time. Four in ten organisations spend at least 41% of their AI project timelines on manual data preparation, and only 39% fall into the report's “digitized and structured” category, where dark data is centrally managed, indexed and ready for analytics and AI.
Fragmentation is the main obstacle: 56% cite information spread across disconnected systems or departmental silos, and 53% point to legacy formats or physical archives. As businesses move towards agentic systems that act across workflows, 70% say they cannot effectively track the lifecycle of the data used in their AI models.
Varun Gupta, Senior Vice President of Global Product and Solutions Marketing at Iron Mountain, said: “AI readiness is about much more than deploying the latest technology.”
Iron Mountain argues that fragmented information also creates security exposure, compliance and audit risk and higher discovery costs, and that organisations need continuous lifecycle governance from creation to destruction.
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