found<\/a> that while 72% of S&P 500 firms flagged at least one material AI risk last year, only 2% cited inaccurate outputs. Not surprisingly, 89% of the survey investors percent expressed concerned about AI accuracy in disclosures, with 47% responding that they watch closely for signs of AI generated errors.<\/p>\nThat\u2019s a risk-laden reporting mess disengaged boards and c-suites need to fix.<\/p>\n
Danger, Danger<\/p>\n
The sharpest division in the Workiva survey results surfaces by rank. Executives were surprisingly very confident in unreviewed AI output at 39%. The confidence of the professionals who handle the underlying data trailed at 29%.<\/p>\n
Steve Soter, Workiva vice president and industry principal treats practitioner caution as competence rather than pessimism. As the people closest to the work grow accustomed to AI, they develop a better understanding of its risks, and \u201cone of the factors that indicate rising maturity is the ability to ask better questions.\u201d <\/p>\n
That leaves the board, the eventual disclosure decision makers, dangerously and distantly holding the least-informed confidence. Asked what single, immediate structural change he would recommend to audit committees, Soter did not hedge.<\/p>\n
\u201cStop accepting general assurances about AI and start requiring evidence. That means asking management, \u2018where is AI being used in financial reporting and disclosure, and what documentation exists to show the output was reviewed and validated?\u2019 Whether the audit committee asks this question, external auditors will certainly be asking, if they haven\u2019t already. If management can’t answer how they are getting comfortable with AI in financial reporting, and prove it with evidence, the committee has found a gap that needs to be closed.\u201d<\/p>\n
Drowning Drops<\/p>\n
AI data governance ups concerns for CEOs and CFOs, the executives who personally sign and certify that quarterly and annual financial reports are fairly presented and that they have established and evaluated disclosure controls and procedures. That mandate did not envision the \u201cblack box\u201d risk of AI reliance.<\/p>\n
\u201cThe rules haven\u2019t changed, but evidence is more critical and more complex than ever before,\u201d Soter argued. Organizations with review checkpoints, validation steps and documentation requirements related to AI-assisted workflows tend to catch errors with well-designed and effective controls. <\/p>\n
\u201cIf management says AI-assisted work was appropriately reviewed, they need to be able to demonstrate that review with documentation. That means being able to trace where the data came from, how the model used it and that a qualified person evaluated the result before it went out the door,\u201d he explained.<\/p>\n
Even with well-governed reporting processes, Soter noted, generic large language models \u201ccan produce polished, inaccurate outputs that give an illusion of quality.\u201d <\/p>\n
\u201cThe most dangerous errors aren\u2019t the ones that are obviously wrong,\u201d Soter warned. “They\u2019re the ones that look right, sound authoritative, and nobody thinks to question. If there\u2019s no way to follow an AI output back to the data that produced it, you may not even know [there\u2019s] a problem.\u201d Especially when the AI outputs reach the boardroom or beyond.<\/p>\n
Three Steps<\/p>\n
Soter offered three actions AI-reliant boards can and should expect from c-suites:<\/p>\n
1. Trace, then certify. Identify every place AI touches financial reporting and disclosure, then determine whether each output can be traced back to source data. The test is whether a CFO can sit across from an investor, auditor or regulator and explain exactly how a number was produced. Any process that fails is unacceptable.<\/p>\n
2. Convert assurance into evidence. Replace management\u2019s verbal comfort with documentation showing what was reviewed, by whom, and against some standard. Review checkpoints, validation steps and retention requirements are what separate an isolated error caught downstream from a pattern that will scream design failure and trigger unwanted disclosures and potential restatements.<\/p>\n
3. Close investor signal gaps. Institutional investors now weigh AI governance<\/a> heavily, even absent a standard disclosure framework. Decide deliberately and decisively what risk factors, homogenized footnotes and curated earnings call commentary convey. Omissions and corporate-speak erode stakeholder confidence.<\/p>\nLeadership\u2019s (in)action that follows will reveal much. Worse it can open preventable exposure for inaccurate disclosure, lax governance and bad decisions. <\/p>\n
What\u2019s really artificial?<\/p>\n","protected":false},"excerpt":{"rendered":"A recent executive survey revealed AI errors have reached boards or external audiences. getty Control failures disclosed by…\n","protected":false},"author":2,"featured_media":149352,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,25,61476,871,41603,428,49755,7168,15585],"class_list":["post-149351","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-artificial-intelligence","tag-boards","tag-cfo","tag-controls","tag-governance","tag-reporting","tag-sec","tag-workiva"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/149351","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=149351"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/149351\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/149352"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=149351"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=149351"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=149351"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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