Talking Tax Plan to Drop 10-Qs Threatens to Trip Up Analysts' AI Models
Oct 29, 2025
Steve Soter, vice president at Workiva and expert in financial compliance, discusses the implications of potentially shifting from quarterly to semiannual 10-Q filings. He warns that this change could undermine AI models that analysts rely on for accurate reporting. Soter explains the benefits of XBRL structured data for machine readability and the risks associated with relying on unstructured text. He advises C-suite leaders on proactive measures to maintain data integrity and ensure transparency, emphasizing the critical need for more frequent, accurate reporting.
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Structured XBRL Is AI's Primary Fuel
- XBRL provides structured, machine-readable financial data that AI models consume more accurately than scraped text.
- Removing quarterly 10-Qs would remove that XBRL feed and degrade AI analysis quality.
Errors Spike Without Structured Data
- AI error rates rise sharply when it scrapes press releases or 8-Ks instead of using XBRL.
- The biggest errors appear in deep notes like segment reporting and revenue detail, not headline statements.
Segment Details Hidden In Notes
- Soter illustrates how segment disclosures live in notes and can vanish from AI view if not structured.
- Analysts needing segment-level detail risk misinterpreting consolidated numbers without those tagged notes.