Cloudera study finds 7% said their data was fully ready for AI

Cloudera published findings from a global study conducted with Harvard Business Review Analytic Services that documented widespread difficulties organizations faced when preparing data for Artificial Intelligence (AI), a condition the report said limited efforts to put AI into routine use.

The study surveyed more than 230 members of the Harvard Business Review audience in October 2025 and found only 7% said their organization’s data was completely ready for AI, while 27% said their data was not very or not at all ready; 73% said their organization should prioritize AI data quality more and an equal share reported that processing and preparing data for AI had been challenging.

Respondents noted that mission-critical data often remained on-premises (on-prem) for reasons the report listed as sovereignty, security, cost, and compliance, and the study stated that bridging that divide required architectures able to operationalize AI across hybrid environments without forcing data movement or compromising control. Cloudera converged public cloud and enterprise data centers to deliver a unified cloud experience across the entire data estate, the release said, and the platform was built on an open-source foundation and powers AI across more than 25 exabytes of enterprise data worldwide.

The report identified top obstacles in preparing data for AI as siloed data or difficulty integrating data sources (56%), a lack of a clear data strategy (44%), data quality or bias issues (41%), and regulatory constraints on data use (34%). It also found that 23% said their organization had an established data strategy for AI adoption while 53% were actively developing one, with protecting sensitive data and privacy (59%), data quality (46%), and data governance (41%) ranking as the most critical components.

“AI is only as powerful as the data behind it,” said Sergio Gago, Chief Technology Officer at Cloudera. “To move from pilots to production, organizations need secure access to 100% of their data, anywhere it resides. Bringing AI to data instead of moving data to your AI is what separates experimentation from enterprise-scale impact.”

The study reported that 65% of respondents expected many business processes would be augmented or replaced by agentic AI within two years and that 47% said their organization believed agentic AI could solve its data quality issues.