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What you are probably seeing
Your spreadsheets update instantly, but the logic behind them is opaque, leaving you unsure if the calculations are actually correct.
You notice discrepancies that appear only after the AI has generated a full model, forcing you to rework entire sections instead of small fixes.
Why it happens
AI tools prioritize speed and pattern matching over deep logical consistency, creating plausible but flawed outputs that bypass standard sanity checks.
Without a clear ownership structure for review, errors propagate through automated workflows without human intervention until they become critical failures.
What changed recently
Step by step
1. Establish a version control system for your financial models to track every AI-generated change against a known good baseline.
2. Define a specific manual audit checklist that verifies input assumptions, formula logic, and output consistency before accepting any AI update.
3. Schedule a dedicated review window where a human expert validates the AI’s reasoning for complex calculations rather than just checking the final numbers.
4. Implement a simple error-flagging mechanism in your workflow that pauses automation when a calculation deviates from expected ranges or patterns.
5. Document the review process and assign a specific person responsible for sign-off on AI-generated model changes to ensure accountability.
Ways to go further
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