Almost all (99%) organisations have dark data, information that is collected and stored but rarely reused, and packed with Redundant, Obsolete, and Trivial (ROT) data, according to a report by Everpure.
The report titled ‘Exploring the enterprise data readiness gap‘, in conjunction with analyst firm Omdia, noted that over half (51-75%) reported that it accounts for over one-third (37%) of all their enterprise data.
“Enterprises cannot build trustworthy AI on untrustworthy data. Redundant, Obsolete, and Trivial (ROT) data creates noise at the very layer that should provide context, increasing the risk of inaccurate AI inference,” said Ashish Gupta, general manager, Data Management, Everpure.
Enterprise data readiness at risk
According to the report, the vast majority (97%) of organisations struggle to transition from AI pilot to production. Over half 62% are facing moderate-to-severe obstacles.
Moreover, 68% of IT leaders consider data management as the top challenge when moving AI into production, and 63%say storage silos and data sprawl are main hindrances to AI success.
While 76% of IT leaders see dark data as a significant business risk and 75% say extracting actionable insight is critical to AI success, over half (58%) of organisations still lack basic visibility into their data environment.
Recommendations
To help organisations assess and remediate their data profiles, Everpure recommends activating sensitive data only under appropriate governance, access controls, and security.
The company also urges organisations to prioritise immediate discovery and activation to accelerate AI initiatives.
It is also vital to secure, minimise, or permanently delete data to reduce liability and compliance exposure, and archive or delete data to cut storage costs and curb data sprawl.
“There is a massive opportunity to turn previously unknown and fragmented data into trusted, contextual intelligence that can support faster AI deployment, better decision-making, and greater business value,” said Simon Robinson, chief analyst at Omdia.
