Data issues stall AI projects at most organisations

Iron Mountain has published research indicating that data issues are delaying or cancelling artificial intelligence projects at most organisations. The study found that 86% of respondents had faced disruption to AI work over the past 12 months.

The findings point to a gap between companies’ stated AI ambitions and the condition of the information needed to support wider deployment. While 95% of organisations said using data to improve business outcomes is a top priority, many are still struggling with fragmented systems, unstructured content and older information stores.

The survey, conducted by Vanson Bourne and commissioned by Iron Mountain, found that 81% of organisations believe AI cannot scale beyond pilot projects unless siloed and unstructured content is turned into AI-ready data. It also showed that only 39% of respondents fall into what the report describes as a “digitized and structured” category, where dark data is centrally managed, indexed and available for analytics and AI use.

Manual preparation remains a significant burden. Four in 10 organisations said they spend at least 41% of AI project timelines on manual data preparation, suggesting much of the work required to move AI projects into production still lies in data handling rather than model development or deployment.