Enterprise AI Pilots Fail Without Strong Data Foundations
Source: SiliconANGLE
Boomi's CEO identifies a constraint on enterprise AI adoption: companies have the tools to build agents but lack the data architecture to feed them reliably. Corporate AI labs are full of stalled projects not because the technology fails, but because 70% of enterprise data remains siloed, duplicated, or poorly governed. The bottleneck has shifted from whether AI works to whether companies can clean, integrate, and govern data at scale, creating an advantage for data infrastructure vendors over AI toolmakers.