India, Oct. 25 -- Iron Mountain's latest research finds that 70% of surveyed organisations cannot effectively track the lifecycle of data used in their AI models, while 86% experienced AI project delays or cancellations because of data concerns over the past year.

The findings, published in The Information Supercycle: Aligning Data, Infrastructure and Capital for AI Scale, expose a gap between enterprise AI ambitions and control over the information supporting them. Although 95% consider using data to improve business outcomes a top priority, many still struggle to make that information accessible, usable, and traceable.

For CIOs, the challenge extends beyond getting an application into production. As AI agents begin acting across busin...