Auditing AI Generated Models
in under 20 minutes

When you would run this workflow

Three scenarios where you have asked AI to draft a model and need to verify it before it leaves your screen.

• Draft 3-statement model from a brief. You asked Claude or ChatGPT to generate a 3-statement model from a one-page memo. The output looks coherent. Before sharing it with your CFO, you need to confirm the formulas actually do what the AI claimed they do.
• Copilot-expanded forecast model. Microsoft Copilot extended your existing forecast across five new product lines. Rows look uniform at a glance, but you have not verified Copilot kept the formula pattern consistent across every cell it touched.
• Junior analyst hands you an AI-assisted model. Your junior used AI to build the bulk of a business case model. They cannot tell you with confidence which formulas are theirs and which came from the AI. You need a workflow that audits the whole thing without depending on provenance.

Why this is hard the traditional way

Auditing an AI-generated model compounds friction at every step:

• ×AI confidently produces formulas that look right but fail at edge cases.
• ×Hallucinated function combinations that work on the sample the AI saw but break on yours.
• ×Highly complex nested formulas (long LET / LAMBDA chains, multi-step IFs, deep INDEX/MATCH) the AI emits as a single 300-character expression you cannot read in the formula bar.
• ×Sign conventions silently inverted. Totals appear consistent because both sides flipped.
• ×Hard-coded plugs the AI inserted when it could not compute a value, buried inside long formulas.
• ×Lookups pointing at ranges or columns the AI invented but never actually created on the source sheet.
• ×Volatile functions (OFFSET, INDIRECT, NOW) the AI uses without flagging the recalculation cost.
• ×Date, unit, and rounding conventions silently inconsistent across sheets the AI generated independently.
• ×No audit trail of what the AI wrote versus what a human wrote.
• ×No way to prove you have checked the AI's work end-to-end.

Worked example

Same audit, two paths. Manual review of the AI's output versus the seven-step workflow.

What to watch out for

• !Excelerate cannot tell you which formulas the AI wrote versus a human, only which ones look suspicious.
• !Style Guard uses conditional formatting; clear its rules via the built-in clear-watermark command before saving the workbook back to a stakeholder.
• !Copilot-generated dynamic arrays sometimes show up as single-cell anchors in the dependency map.
• !Volatile functions (OFFSET, INDIRECT, NOW) can change the dependency map between runs. The map captures the current state.
• !Excel Tables (structured references) are mapped as their own nodes, not as cell ranges.
• !Models with circular references are flagged separately. Excelerate does not auto-resolve circulars.
• !3D references (Sheet1:Sheet5!A1) are enumerated by tab position, including hidden and very-hidden sheets.

Frequently asked questions

• How long does this audit actually take?

  Around 18 minutes for a typical AI-generated 40-tab financial model. The dependency map renders in about 10 seconds. Most of the time is judgement on the formulas the workflow flags, not waiting on the tools.

• Does Excelerate change anything in the workbook during the audit?

  Only one thing. Style Guard applies temporary colour-coded conditional formatting you can clear in one click. Everything else is non-destructive: the dependency map and the Logical Flow Map render inside the Task Pane; the inconsistency and orphan scans report findings without touching cells. You only modify the workbook when you act on a finding yourself.

• Can Excelerate tell which formulas came from the AI?

  No. Excelerate flags formulas that deviate from the patterns and principles of a well-built model, regardless of whether the deviation came from an AI, a hurried analyst, or a copy-paste. That is the right lens for this workflow: you should not have to trust provenance to trust the model.

• Does this catch hallucinated functions from ChatGPT or Claude?

  Yes, indirectly. Hallucinated function combinations either #REF! at execution (the inconsistency detector flags them) or return plausible-but-wrong values that surface as pattern breaks across rows (the detector flags those too). The Formula Deconstructor then lets you read the AI's intent in plain English, and the Logical Flow Map confirms each reference actually goes where the AI claimed.

• Why not just ask the AI to double-check its own work?

  AI marking its own homework is a known failure mode. The model that produced the error is the same model evaluating it, and tends to defend its own output. An independent audit lens, pattern-based and principles-based, catches what the AI will not flag on itself.

• Will this work on Excel for Windows, Mac, and the web?

  Yes. Excelerate is an Excel add-in and runs on Excel for Windows, Mac, and Excel for the web. All seven tools in the workflow have parity across all three.

• How is this different from Excel's built-in formula auditing tools?

  Excel's Inquire add-in shows precedents and dependents one cell at a time, in a dialog. Excelerate shows you the whole workbook as a graph in a single view, role-codes each sheet, traces precedent chains across sheets in one laser, and ranks formulas by suspicion across the whole model. Different lens, built for a different scale of question. And built for the era where the workbook may not have been written by a human.