Nearly every enterprise is investing in AI, but only 5% say their data is ready

"Nearly halfway into 2026, enterprises are beginning to see tangible returns on their AI investments. Yet many are discovering that scaling requires something far less glamorous than flashy frontier models and state-of-the-art benchmarking: Clean, interoperable, governed data."

""You do not need enterprise-wide AI-ready data to launch pilots or isolated AI use cases," said Cayetano Gea-Carrasco, Dun & Bradstreet's chief strategy officer. "But you do need it to scale AI reliably across mission-critical workflows and systems.""

"According to a new AI Momentum Survey from Dun & Bradstreet, 97% of organizations report active AI initiatives, but just 5% say their data is ready to support them. This reflects the messy reality of AI as enterprises struggle to move beyond experimentation to operationalization."

"This is for a variety of reasons, including problems with access to data (reported by 50% of those polled by D&B), privacy and compliance risks (44%), and data quality and integrity concerns (40%). Furth"

Nearly half of 2026 shows enterprises beginning to see tangible returns from AI investments. Many organizations find that scaling depends less on advanced frontier models and benchmarking and more on clean, interoperable, governed data. A survey reports 97% of organizations have active AI initiatives, while only 5% report data readiness to support them. Early pilots and isolated use cases can start without enterprise-wide AI-ready data, but scaling across mission-critical workflows requires it. Early ROI appears uneven, with 67% seeing early pockets of returns and 24% reporting broad or strong returns. Data access, privacy and compliance, and data quality and integrity are major barriers, with access cited by 50%, privacy and compliance by 44%, and data quality by 40%.

Read at Computerworld