JACKSONVILLE, Fla., July 28, 2026 /PRNewswire/ -- More than three-quarters of enterprises now report some measurable ROI from AI, according to Dun & Bradstreet's latest AI Momentum survey. The largest share, 48%, report "pockets of ROI" while 28% report "broad" or "strong" ROI across multiple projects. At the same time, only 6% say their enterprise data is "fully ready" to support AI at scale.

The findings suggest that enterprise AI is entering a new phase of maturity, as organizations are increasingly seeing value from AI, but still face a harder challenge in scaling those returns consistently across the enterprise.

That same pattern is visible in how organizations are progressing with AI deployments. More are moving beyond planning and piloting, with the share "scaling AI" rising to 34%. As pilot AI projects move further into production, the central question becomes whether organizations can extend that value across departments. That will depend on closing the data readiness gap.

While the majority of organizations describe their enterprise data as either "partially" (47%) or "mostly" (36%) ready for AI, only 6% say it is "fully ready" to support AI at scale. Realizing the broad ROI across enterprise AI projects will depend on closing the data readiness gap. Models require the business context to be consistent, accurate, and reliable enough to support decisions across teams, systems, and agentic use cases.

"The challenge now is that AI adoption has outpaced data readiness. That is why only a few organizations have turned pilots into P&L-level ROI. Today's frontier models are extremely capable, but getting the context right is the key to effectiveness. Grounding AI in verified information, so facts can be confirmed and integrations can be established, is fundamental to adoption of agentic workflows," said Gary Kotovets, Chief Data and Analytics Officer at Dun & Bradstreet. "That is the opportunity that D&B is built to address. Our identity infrastructure grounds AI in real, verified business context, minimizing hallucinations and giving organizations the confidence to let their agents work for them. The D&B Commercial Graph™ pre-resolves crucial business context for AI, so you don't have to burn tokens rediscovering and reconciling across departments."

Key findings include:

AI ROI is visible, but uneven

More than three-quarters of organizations report at least some measurable ROI from AI initiatives.
The largest share, 48%, report "pockets of ROI," with some pilots showing returns.
28% report "broad" or "strong" ROI across multiple projects.

AI deployment is moving into production

Nearly all organizations report active AI initiatives.
34% are scaling AI into production.
More than half are either scaling AI into production, operationalizing AI across multiple core processes, or using agentic AI workflows.

Enterprise data is not yet fully ready for AI at scale

Only 6% of organizations report their enterprise data is fully ready to support AI at scale.
47% describe their enterprise data as partially ready, while 36% describe it as mostly ready.
The findings suggest a wide gap between data that can support early AI progress and data that is ready to support scaled, repeatable ROI across the enterprise.

In 2026, Dun & Bradstreet's AI Momentum Survey has shown steady progress in AI adoption and maturity, even as data readiness remains challenged. The Q3 findings suggest the next phase will require organizations to improve data readiness to turn early and uneven ROI into more consistent returns at enterprise scale. That will require confidence in the context behind AI: data that is complete, current, and reliable enough to support decisions across teams, systems, and use cases.

The Dun & Bradstreet AI Momentum Survey is a quarterly global survey of 10,000 businesses across 32 countries that tracks enterprise AI adoption, investment, deployment, and business outcomes over time.

About Dun & Bradstreet

Dun & Bradstreet provides the verified commercial identity foundation for enterprises to deploy AI at scale. The company originated the D‑U‑N‑S^® Number in 1963, now the global standard for identifying commercial entities. Anchored by this identifier, the D&B Commercial Graph structures and connects business identity consistently across systems, enabling AI to operate on accurate, validated data. Since 1841, businesses of every size have relied on Dun & Bradstreet to navigate change and accelerate growth. For more information, visit www.dnb.com.

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SOURCE Dun & Bradstreet, Inc.