Companies Are Scaling AI on Data They Don't Trust, New Study Finds

Nearly half of 350+ Finance and IT Executives surveyed made major business decisions on faulty data in the past year; those burned by bad data use the most AI tools

BIRMINGHAM, Mich., May 5, 2026 /PRNewswire/ -- OneStream, the leading enterprise finance management platform that modernizes the Office of the CFO by unifying core finance and operational functions, today announced the results of a new study examining the state of data governance across the enterprise. The study, which polled over 350 senior Finance and IT executives — including CFOs, CAOs, CTOs, CIOs, Chief Digital Officers, Chief Data Officers, and Chief AI Officers across the U.S., U.K., and France — reveals how poor data practices are undermining AI adoption and driving significant financial risks to their organizations.

With AI spending forecasted to surpass $2 trillion in 2026, organizations are under mounting pressure to deploy AI at scale. Yet the research suggests the data foundation most are building on is fundamentally unstable. While nearly all executives (96%) view accurate, trusted data as very or extremely important to their organization's success, nearly half (47%) admit they have made a material business decision based on inaccurate, incomplete, or outdated financial data in the past 12 months.

The consequences are significant:

• Nearly three in four executives (72%) say bad data cost their organization $500,000 or more, with more than one-third (37%) reporting damages over $1 million.
• Downstream impacts include: more than four in 10 (44%) delayed reporting and closing, while over one-third cite lost revenue opportunities (41%), a lack of trust in automated insights (38%), and compliance issues (35%).

Despite these risks, companies are not slowing down. Executives who have made decisions on bad data are four times more likely to use ten or more AI tools than their peers. At the same time, confidence is fragile—an overwhelming 95% of these executives report concerns about AI-related risks, including flawed decisions (37%) and one in five (20%) cites financial misreporting.

"Nearly half of executives admit they've made decisions on bad data, yet AI adoption continues to accelerate. Unless companies have data they can trust, AI will only accelerate and amplify bad decisions," said Tom Shea, CEO of OneStream. "No enterprise can start from scratch to unify all its data—it's not practical. The advantage comes from aligning Finance and IT to focus on the areas where the business logic and financial context are clear, and applying AI that understands how those decisions are made. Without that, AI risks amplifying errors instead of improving outcomes."

Emerging Blind Spot: High Confidence, Low Trust in the Age of AI
As boards demand faster execution and measurable AI ROI, a clear gap is emerging between AI ambition and data readiness. Nearly four in five executives (79%) believe their data governance can support large-scale AI adoption and 85% say they have a formal program in place or underway, but that confidence breaks down in practice. Nearly two-thirds (61%) of executives second-guess their data at least once a month and over 1 in 10 (11%) question it daily.

The issue is structural. Today, just 19% pull the majority of their AI inputs from a single, centralized enterprise system. Further, only half have established a consistent source of truth, implemented data quality rules, or automated reconciliation across systems. As a result, disconnected systems and lack of integration (32%) were cited among the top barriers to effective governance. AI is often deployed on shaky data - amplifying errors rather than eliminating them.

Speed vs. Structure: Why AI Fluency Isn't Enough
The data accuracy challenges become more visible where technical fluency outpaces institutional knowledge. While AI enables faster analysis, it cannot replace the business context required to recognize when data is incomplete or misleading.

Rising leaders (ages 25–44) are heavier AI users—over four in five (82%) use three or more AI tools for decision-making, compared to 69% of more experienced peers. Yet they are also more exposed to risk: over half (51%) report making a material decision based on faulty data, versus 39% of older leaders.

The consequences are more severe as well. Younger executives are over four times more likely to report significant financial or compliance impacts (17% vs. 4% among seasoned peers), and twice as likely to cite a loss of trust in AI outputs (44% vs. 22%).

This highlights a critical gap: AI proficiency alone is not enough. Without strong governance and business context, the leaders most equipped to use these tools are also the most vulnerable to their risks.

A Shared Challenge Viewed Differently
While Finance and IT are aligned in recognizing the importance of data governance, and most (89%) executives claim Finance and IT are aligned, 85% of CIOs believe they lead data governance, while 78% of CFOs claim the lead. They also have a different perspective on data governance challenges: Finance prioritizes accuracy, context, and accountability, and IT focuses on enablement, scalability, and execution. Because of this disconnect, nearly 1 in 3 CFOs (32%) cites "lack of data ownership" as a key barrier to success.

However, when Finance and IT come together, the impact is significant: organizations that achieve complete alignment between Finance and IT are 5.5x more likely to report complete trust in their data. Closing this gap is what turns governance from a program into a true foundation for AI-driven decision-making.

"Every generation of finance leaders has had to earn trust in the numbers before they could act on them. What's different today is that AI has compressed that timeline dramatically, and the margin for error has shrunk with it," said Pam McIntyre, Chief Accounting Officer at OneStream. "The next generation of finance leaders is inheriting AI tools that can do extraordinary things, but those tools require a level of data discipline that has to be built deliberately, with clear ownership, clear definitions, and a governance structure that Finance and IT build together."

Survey Methodology

The research was conducted online in the U.S., U.K., and France by The Harris Poll on behalf of OneStream among 352 executives employed full-time as a Chief Finance Officer, Chief Accounting Officer, Chief Technology Officer, Chief Information Officer, Chief Digital Officer, Chief Data Officer, or Chief AI Officer at businesses with 100 or more employees and revenue of $50 million or more. The survey was conducted March 16–19, 2026. Raw data were not weighted and are therefore only representative of the individuals who completed the survey.

About OneStream

OneStream is how today's Finance teams can go beyond just reporting on the past and Take Finance Further by steering the business to the future. It's the leading enterprise Finance platform that unifies financial and operational data, embeds AI for better decisions and productivity and empowers the CFO to become a critical driver of business strategy and execution.

We deliver a comprehensive cloud-based platform to modernize the Office of the CFO. Our Digital Finance Cloud unifies core financial and broader operational data and processes and embeds AI for better planning and forecasting, with an extensible architecture, so customers can adopt and develop new solutions, achieving greater value as their business needs evolve.

With over 1,800 customers, including 18% of the Fortune 500, a strong ecosystem of go-to-market, implementation, and development partners and 1,600 employees, our vision is to be the operating system for modern Finance. To learn more, visit onestream.com.

Media Contact

Jaclyn Proctor
Media Relations Contact
OneStream
[email protected]

SOURCE OneStream, Inc.