3-day Virtual Seminar

AI Gave Me the Formula-Can I Trust the Answer?

Overview

This session picks up where prompting tutorials end. Attendees use an AI assistant to produce a real analysis, then subject that analysis to a structured verification routine - control totals, invariant tests, boundary cases, hand-checked samples, and a recorded evidence log - before accepting a single number. The subject is not whether to use AI. It is what has to be true before you put your name on its output.

Why you should Attend

AI errors in Excel do not announce themselves. They arrive as a correct-looking result computed over the wrong range, a lookup that silently returns the nearest match, or an aggregation that quietly drops the rows it could not classify. You will not catch these by reading the formula, because the formula reads as though it works. Anyone accepting AI-generated analysis without a verification routine is signing their name to arithmetic they have not checked.

Areas Covered in the Session

• The C.H.E.C.K. framework: Control totals first, Hold the boundaries, Examine a sample by hand, Compare against an invariant, Keep the evidence log
• How AI errors actually present in Excel: right function, wrong range; approximate match; silently dropped rows; confidently fabricated logic
• Building the control total before you build the analysis, so the check is not derived from the thing it is checking
• Invariant tests: relationships that must hold regardless of the data, and what it means when one breaks
• Boundary and edge cases - blanks, zeros, negatives, duplicates, text stored as numbers, and dates that are not dates
• Hand-reconciling a deliberate sample: how many rows, chosen how, and what a clean sample does and does not prove
• Asking the assistant to explain its own logic — useful as a prompt for your review, worthless as evidence on its own
• The evidence log: recording the prompt, the output, the checks run, the results, and the accept-or-reject decision
• Knowing when to stop verifying: matching the depth of the check to the consequence of being wrong
• Where AI genuinely earns its place in analytical work, and where the verification cost exceeds the time saved
  

Who Will Benefit

• Financial Analysts, Controllers, and Accountants
  
• Business and Data Analysts
  
• Business Intelligence and Reporting Professionals
  
• Internal Auditors and Compliance Analysts
  
• Operations Managers using Excel for reporting
  
• Project Managers and PMO Analysts
  
• IT and Data Leaders setting organizational AI usage policy