A new report from Cloudera based on a new global study conducted by Harvard Business Review Analytic Services, of more than 230 members of the Harvard Business Review audience, all involved in their organization’s AI data decisions, finds that just seven percent of enterprises say their data is completely ready for AI.
While organizations are accelerating AI initiatives, their underlying data foundations are not keeping pace. 27 percent report their data is not very or not at all ready, highlighting a growing gap between AI ambition and operational readiness. 73 percent of respondents say their organization should prioritize AI data quality more than it currently does
Top obstacles when it comes to preparing data for AI include: siloed data/difficulty integrating data sources (56 percent), lack of a clear data strategy (44 percent), data quality/bias issues (41 percent) and regulatory constraints on data use (34 percent).
While only 23 percent say their organization has an established data strategy for AI adoption, more than half (53 percent) are actively developing one. Protecting sensitive data and privacy (59 percent), data quality (46 percent), and data governance (41 percent) rank as the most critical components of these strategies.
There are high hopes for agentic AI too. 65 percent of respondents expect many of their organization’s business processes will be augmented or replaced by agentic AI in the next two years. While 47 percent say their organization believes agentic AI can solve its data quality issues.
“AI is only as powerful as the data behind it,” says Sergio Gago, chief technology officer at Cloudera. “To move from pilots to production, organizations need secure access to 100 percent 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.”
You can get the full report from the Cloudera site.
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