Although 84% of executives are at least somewhat confident in AI output without human review, only 11% believe their data quality is sufficient for AI use

NEW YORK--(BUSINESS WIRE)--

Workiva Inc. ( WK ) , a leading, audit-ready platform for trust, transparency, and accountability, today released findings from its 2026 Midyear Executive Benchmark Survey.

Although 84% of surveyed executives say they are at least somewhat confident in the accuracy of AI output without human review, one in four (26%) say internal audits have detected AI errors that reached external audiences or board members. This data suggests there is a disconnect between what executives believe and what evidence shows. As AI reshapes the enterprise at unprecedented speed, a new risk is emerging: transformation could be outpacing the instincts of the leaders tasked with overseeing it.

"Confidence in AI without control over data quality is a liability, not a strategy. CFOs need platforms that connect AI to trusted, auditable data so every output is one they can verify and every disclosure is one they can defend," said Barbara Larson, Chief Financial Officer at Workiva ( WK ). "Getting this right is about more than avoiding errors. Business leaders can move faster and embed AI deeper into their operations when they trust what their systems produce. That's a real competitive edge."

Data Quality Threatens AI Accuracy and Investor Trust

Executives largely agree that poor data quality is limiting their organizations’ use of AI, suggesting enterprise AI can only scale where there is confidence in, and control over, the underlying data. Institutional investors express similar concerns about the accuracy of AI-generated content.

Only 11% of executives believe their data quality is sufficient for AI use

27% say poor data quality has significantly blocked deployment in key workflows

71% say poor data quality has at least moderately impacted the use of AI in financial and sustainability reporting

89% of investors are concerned about AI accuracy in corporate disclosures

Over time, weak or unverifiable data may erode credibility with stakeholders, and organizations that fail to address data quality and investor concerns risk losing ground to more proactive peers.

As AI Use Grows, Executives Call for Supporting Infrastructure

For financial reporting teams, and CFOs in particular, the tools that govern AI output are as critical as the AI itself. As agents become more autonomous, executives believe the need for specialized infrastructure will increase, citing multiple priorities1:

49% say they will continue to need systems of record, such as general ledgers

45% say they will need software that enables traceability and audit

55% say they will need platforms to manage agents and automated workflows

"Generic AI isn't enough for financial reporting. Investors, regulators, and boards expect answers they can trust. The real advantage comes from specialized AI built on governed, auditable data and paired with human judgment, giving organizations the confidence to verify what AI produces and stand behind the decisions and disclosures that follow,” said Jason Darby, Chief Financial Officer of Amalgamated Bank.

The Workiva ( WK ) 2026 Midyear Executive Benchmark Survey polled 2,272 finance, risk, and sustainability professionals, including 847 C-level executives, from organizations across North America, Latin America, Europe, and the Asia Pacific region. The survey also polled 367 institutional investors from firms in North America and the United Kingdom. Read the report at www.workiva.com/benchmark-2026.

About Workiva ( WK )

Workiva Inc. ( WK ) powers trust, transparency, and accountability. Finance, accounting, sustainability, risk, and audit teams from more than 6,700 organizations, including over 85% of Fortune 1,000 companies, rely on Workiva ( WK ) for their mission-critical work. We transform how customers connect data, unify processes, and empower teams in a secure, audit-ready platform. Learn more at workiva.com.

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Source: Workiva Inc. ( WK )