AI in Excel: Generated Formulas Still Need Spreadsheet Review Evidence
Published August 2026 by Solarc Labs
AI changes how spreadsheet work is produced, not the need to review it
ICAEW updated its Spreadsheet Competency Framework in July 2026 to reflect automation and AI, including new competencies for using the technology safely and effectively in spreadsheet work. Its audit-reviewer guidance specifically warns about over-reliance on automated outputs, data bias and lack of transparency in AI-generated results. The practical consequence is simple: faster formula generation does not turn the resulting workbook into verified evidence.
A formula that returns a plausible number can still encode the wrong logic
ICAEW’s 2026 discussion of AI in Excel gives examples where AI can take shortcuts, insert a dead value instead of the required formula, or generate formulas that are difficult for experienced users to understand. Those failures are dangerous precisely because the output can look finished. Review the logic path, not only the displayed result. Trace precedents and dependents, inspect hard-coded values, compare formulas across repeated regions and challenge whether the calculation answers the intended business question.
Prioritize critical outputs rather than pretending every cell was proven correct
ICAEW’s spreadsheet-review guidance notes that large workbooks can contain thousands of distinct formulas, making exhaustive manual validation impractical. It recommends targeting critical areas and outputs through staged structural, data, analytical and detailed review. A useful assurance workflow therefore starts with workbook purpose, critical sheets and decision outputs, then uses deterministic checks to focus human attention. “No finding” must remain different from “the workbook is proven correct.”
Preserve the workbook version and the reviewer decision
AI-assisted edits can make it even more important to know which workbook state was reviewed. Capture the exact version or fingerprint, the deterministic findings, the critical outputs checked, the human dispositions and the post-remediation re-run. That evidence lets a later reviewer reconstruct what was inspected without needing to trust a generic “AI checked” or “audit passed” label.
SheetReliability supports reproducible findings, not spreadsheet correctness certification
SheetReliability is positioned as a spreadsheet-assurance workflow: freeze the workbook version, run deterministic checks, record reviewer decisions for material findings and re-run verification after remediation. It should not silently rewrite cells or claim that absence of a deterministic finding proves the workbook correct. AI-generated formulas fit that same boundary. The product can help make review evidence reproducible; the finance, risk or audit owner remains responsible for the business assumptions and consequential conclusion.
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