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Data Quality

A white globe with continents made of blue dots, from the cover of a SAS and IDC report on trust in agentic AI

IDC Report Finds Businesses Give AI Agents Decision Roles As Trust Lags

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Nearly 9 in 10 organizations said AI agents play some role in decisions, but only 66% of respondents said they trust agentic AI.

 

Key Takeaways

  • An IDC survey found that 89% of organizations give AI agents some role in decisions, while 66% of respondents trust agentic AI.
  • 79% of respondents said people override AI recommendations in more than 10% of cases, most often because the result lacks an explanation or important context.
  • Only 17.5% said their organizations had fully optimized their data systems.

A new SAS report from IDC found that companies are allowing AI agents to influence or make decisions faster than trust in those systems is developing.

The report is based on an April 2026 IDC survey of 2,699 decision-makers across 28 countries. It focused on banking, insurance, life sciences, and the public sector.

Decision-making authority expands faster than trust

Survey respondents said AI agents play a role in decisions at 89% of their organizations, from recommending actions for people to approve to acting without prior approval.

Only 66% said they trust agentic AI, leaving a 23-percentage-point gap between reported use and reported trust. Agentic AI also trailed generative AI, which 76% said they trust.

Users intervene when AI cannot explain its work

The survey found that 79% of respondents override AI recommendations in more than 10% of cases.

The leading reason was insufficient explanation, cited by 34.5%. Another 25.6% said an AI result failed to account for the full context of the decision. Factual errors ranked lower, at 14.8%.

Data systems remain a governance weakness

Only 17.5% of respondents said their organizations had fully optimized their data systems. The report said mature data systems make it easier to trace information to its source and continually check whether an AI system is producing reliable results.

Stronger governance is associated with higher reported returns

Organizations with the strongest AI governance practices were far more likely to report high returns on their AI spending. The report gave higher scores to organizations with stronger controls over the data AI uses, how it reviews decisions, and who is accountable for its use.

Among the highest-scoring organizations, 62% reported earning at least $2 for every $1 spent on AI, compared with 4% of the lowest-scoring organizations.

The survey does not establish that stronger governance caused the higher returns.

The report said 86% of organizations plan to increase spending on AI oversight, data quality, validation, and accountability during the next year. It did not specify how much each organization plans to spend.

Green reporting dashboard illustrating data quality, AI errors, and corporate disclosures in Workiva’s 2026 survey.

84% of Executives Trust AI Content In Annual Reports, But 26% Say Errors Reached Boards

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Poor data quality has limited AI use in financial and sustainability reporting for 71% of surveyed executives, while 89% of institutional investors are concerned about AI accuracy in company disclosures.

Key takeaways

  • 84% of surveyed executives said they were somewhat (45%) to very confident (39%) that AI-generated information could appear in an annual report without human review.
  • 26% said internal audits detected AI errors that reached external audiences or the board.
  • 71% of surveyed executives said poor data quality had limited AI use in financial and sustainability reporting, while 47% of institutional investors said they actively look for AI-generated errors in company disclosures.

Workiva’s 2026 Midyear Executive Benchmark Survey found a wide gap between executives’ confidence in unreviewed AI material and the AI errors their organizations identified.

The survey found that 84% of executives were at least somewhat confident in the accuracy of AI output appearing in an annual report without human review. At the same time, 26% said internal AI audits detected errors that reached external audiences or the board.

Executives trust AI output despite detected errors

The 84% confidence figure included 39% of executives who said they were very confident and 45% who were somewhat confident in unreviewed AI-generated information.

The survey also asked professionals below the C-suite the same question. Among that group, 76% were at least somewhat confident, including 29% who were very confident.

The report does not say that all detected AI errors appeared in annual reports. It also does not describe the type or severity of the errors that reached outside audiences or boards.

Poor data quality limits AI reporting

Only 11% of executives said their organizations’ data quality was sufficient for AI use.

Another 71% said poor data quality had at least moderately limited AI use in financial and sustainability reporting. That included 27% who said poor data had substantially blocked AI use in important business processes.

Investors scrutinize AI-generated disclosures

Investors are paying close attention. In the survey, 89% said they were concerned about AI errors in company disclosures, and 47% said they actively check those disclosures for signs of AI-generated mistakes.

The survey also found that 96% considered company policies for AI governance and human oversight important to their investment decisions. That included 62% who considered those policies very important.

Workiva surveyed 2,272 finance, risk, sustainability, and legal professionals, including 847 C-level executives, plus 367 institutional investors. The investor sample covered the United States, Canada, and the United Kingdom. The professional respondents worked at organizations with at least 250 employees or $250 million in annual revenue across North America, Latin America, Europe, and the Asia-Pacific region.