A new survey commissioned by Parseur exposes a disconnect in organizational data confidence: although 88% of U.S. business leaders express confidence in the accuracy of data powering their analytics and AI systems, the same percentage acknowledge they still encounter errors in document-derived data.
The findings suggest that confidence in data quality may be masking widespread accuracy issues in the data feeding business systems. Nearly seven in ten respondents (69%) reported finding errors sometimes, often, or very often, indicating these issues are not isolated incidents but a routine part of day-to-day operations.
These data quality gaps carry significant consequences. Respondents linked document data errors to incorrect forecasts, financial reporting issues, customer or supplier disputes, compliance or audit findings, operational delays, revenue loss and increased fraud exposure. Many described the impact of these errors as moderate or severe, highlighting the operational and financial risks of unreliable data.
The survey results arrive amid widespread AI adoption across business functions. While organizations continue to expand their use of AI-driven tools, the data feeding those systems often originates from documents such as invoices, purchase orders, contracts, and customer forms. Errors in data inputs can quietly undermine AI outputs, analytics, and downstream decisions, even when overall confidence in data remains high.
“What this survey shows is a confidence illusion,” said Sylvestre Dupont, co-founder and CEO of Parseur, an intelligent document processing platform. “Organizations believe their data is healthy, but persistent errors tell a different story. As companies rely more heavily on AI, data accuracy becomes foundational. That’s why organizations need better support around how data is captured and validated at the point of entry.”
The survey also identified clear “danger zones” in document accuracy. Invoices were cited most often as error-prone (21%), followed by purchase orders (18%) and customer-facing documents (17%). Respondents also flagged contracts, intake forms and logistics documents as frequent sources of errors, underscoring that data quality challenges extend beyond a single workflow.
Methodology
In December 2025, Parseur partnered with QuestionPro to survey 500 U.S.-based professionals involved in document-heavy workflows, including operations, finance, administration, IT, customer support, and related functions. Respondents primarily included C-suite and executive leaders, directors, and managers. Participants represented a broad range of industries, with the strongest participation from technology, finance, and logistics, as well as healthcare and other sectors.
Learn more about how improving data feeding accuracy can reduce errors and strengthen analytics and AI performance across organizations, at the website here.
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