AI failures often trace back to poor data foundation: survey
Dive Brief
More than half of enterprises are working to establish clear lines of internal accountability for AI outputs, a Collibra study conducted by Harris Poll found.
Published Sept. 17, 2026
Dive Brief:
- When enterprise AI initiatives fall short, 72% of AI decision-makers said the root cause stems from a poor data foundation, according to a Harris Poll survey of 300 employees in data management and privacy, as well as AI decision-makers. The survey was conducted on behalf of software company Collibra.
- Decision-makers are restructuring operating models to better align intelligence and data governance as a result, the survey found. For 53% of decisions-makers, that means moving the reporting line for their AI functions closer to the data organization. Among enterprises, 58% are focused on establishing a clear line of internal accountability for AI outputs.
- “Enterprises need to know which agents are operating, who owns them, what data and...
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