IBM: Data silos are holding back enterprise AI

According to IBM, the primary barrier holding back enterprise AI isn’t the technology itself but the persistent issue of data silos.

Ed Lovely, VP and Chief Data Officer at IBM, describes data silos as the “Achilles’ heel” of modern data strategy. Lovely made the comments following the release of a new study from the IBM Institute for Business Value that found AI is ready to scale, but enterprise data is not.

The report, which surveyed 1,700 senior data leaders, found that functional data remains stubbornly isolated. Finance, HR, marketing, and supply chain data all operate in isolation, with no common taxonomy or shared standards.

This fragmentation is having a direct, negative impact on AI projects. “When data lives in disconnected silos, every AI initiative becomes a drawn-out, six-to-twelve-month data cleansing project,” said Ed Lovely, VP and Chief Data Officer at IBM. “Teams spend more time hunting for and aligning data than generating meaningful insights”.

This is a direct threat to competitive advantage. For CIOs and CDOs, the mission is no longer just to collect and protect data, but to deploy it effectively to power these new AI systems.