Bad Data Keeps Enterprise AI Stuck in Pilots

Enterprises have invested billions in AI infrastructure, yet most deployments remain stuck in experimentation. According to an IDC survey, 94% of IT leaders cite data quality as the primary factor in AI success, but most enterprise data remains unclassified, ungoverned and unfit for production workloads. Pure Storage and Nvidia are jointly addressing this through co-engineered data intelligence, vectorization, and GPU-accelerated inference pipelines. Pure Storage's newly announced Data Stream product aims to reduce raw data preparation from months to minutes, automating the full pipeline so AI models run against curated, high-context datasets rather than disconnected silos.