Enterprise Data Readiness Linked to AI Returns

Only 8% of enterprises say their data is ready to support AI, while 33% describe it as mostly ready and 44% as partially ready, according to a Dun & Bradstreet survey of 10,000 businesses across 32 countries. Among companies with fully AI-ready data, 81% report strong returns on AI investments, compared with 12% of companies whose data is partially ready. Dun & Bradstreet chief data and analytics officer Gary Kotovets said organizations with AI-ready data see broad returns at a much higher rate.

Businesses in the Americas were more likely to increase AI spending, while reporting the second-lowest rates of strong returns and of mostly or fully AI-ready data. Kotovets said the next phase of AI adoption will depend less on access to models and more on the quality of information those models can use.

A Collibra report found that 72% of surveyed AI decision-makers cited poor data foundations as a common reason enterprise AI initiatives fall short. A lack of structured context also contributes to more manual supervision by IT teams overseeing AI agents. An August report by Google Cloud and MIT Technology Review Insights said businesses need a fuller understanding of their enterprise data, including unstructured data, to build the quality and trust needed to deploy agents at scale; only 10% of companies had widely scaled agents across their businesses. Heineken made data foundations a key part of its AI work. At an October Gartner IT Symposium/Xpo, U.S. CIO and digital technology SVP Frank Iannella said his team aimed to create decision-ready data aligned with business use cases, assessing whether information was current, fit for action and connected to the right use cases.

Only 8% of enterprises say their data is ready to support AI, while 33% describe it as mostly ready and 44% as partially ready, according to a Dun & Bradstreet survey of 10,000 businesses across 32 countries. Among companies with fully AI-ready data, 81% report strong returns on AI investments, compared with 12% of companies whose data is partially ready. Dun & Bradstreet chief data and analytics officer Gary Kotovets said organizations with AI-ready data see broad returns at a much higher rate.

Businesses in the Americas were more likely to increase AI spending, while reporting the second-lowest rates of strong returns and of mostly or fully AI-ready data. Kotovets said the next phase of AI adoption will depend less on access to models and more on the quality of information those models can use.

A Collibra report found that 72% of surveyed AI decision-makers cited poor data foundations as a common reason enterprise AI initiatives fall short. A lack of structured context also contributes to more manual supervision by IT teams overseeing AI agents. An August report by Google Cloud and MIT Technology Review Insights said businesses need a fuller understanding of their enterprise data, including unstructured data, to build the quality and trust needed to deploy agents at scale; only 10% of companies had widely scaled agents across their businesses. Heineken made data foundations a key part of its AI work. At an October Gartner IT Symposium/Xpo, U.S. CIO and digital technology SVP Frank Iannella said his team aimed to create decision-ready data aligned with business use cases, assessing whether information was current, fit for action and connected to the right use cases.