Eighty-four percent of executives say they are confident in AI output without human review. One in four of those same executives report that internal audits have caught AI errors that made it to external audiences or board members. Workiva's 2026 Midyear Executive Benchmark Survey, polling 2,272 finance, risk, and sustainability professionals alongside 367 institutional investors, puts those two figures in the same document.
The survey, covering organisations across North America, Latin America, Europe, and Asia Pacific, surfaces a secondary problem under the confidence gap: data quality. Only 11 percent of executives believe their organisation's data quality is sufficient for AI use. Twenty-seven percent say poor data quality has significantly blocked AI deployment in key workflows. Seventy-one percent say it has at least moderately affected AI use in financial and sustainability reporting.
Institutional investors are tracking the same concern from the outside. Eighty-nine percent say they are worried about the accuracy of AI-generated content in corporate disclosures, a figure that sits alongside growing regulatory pressure to treat AI outputs as auditable records rather than drafts.
The infrastructure question emerging from the survey is what comes next as AI agents take on more autonomous roles in financial reporting. Asked what tools they expect to keep needing, 55 percent of respondents said platforms to manage agents and automated workflows, 49 percent said systems of record such as general ledgers, and 45 percent said software enabling traceability and audit. Respondents could select multiple answers.
The full benchmark report is at workiva.com/benchmark-2026.
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