How to verify AI-generated Office files before they ship — AI Summary

Summary

Don't just prompt AI for a finished document. To ensure accuracy in Excel and PowerPoint, you must build a multi-stage, agentic workflow that treats knowledge work like code—preparing sources, defining structural blueprints, and enforcing adversarial verification before final output.

Key Topics

• Source Preparation: This involves creating an inventory of your data, including owners, dates, and types, so the model isn't guessing which file is the ground truth. It acts as the anchor for all subsequent work.
• Hostile Reviewer Prompt: By instructing the model to 'identify every issue without fixing anything', you change its objective function from generation to verification. This is the most effective way to catch surface-level hallucinations.
• Task-Risk Gradient: Formatting and chart layout are low-risk tasks where AI excels, whereas numerical synthesis and regulatory language are high-risk. Assigning human review burden based on this gradient ensures efficiency without sacrificing accuracy.
• File Specification: For presentations, this means a list of claims and evidence; for spreadsheets, it's a diagram of tab architecture. Building this ensures the finished product is logically sound.

Key Takeaways

• Audit your current AI workflow by introducing a source inventory step.
• Apply the 'hostile reviewer' prompt to your next important document.