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Module
Module 3 of 5Lesson 2 of 3~15 min

Have AI build a yield spreadsheet, then check it

AI can put together a yield spreadsheet in minutes, but one wrong formula is enough to mislead a client. This lesson shows you how to get the structure, test it against a case you already know and spot the usual errors. You then produce several scenarios and a careful client summary.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to have AI generate the structure and formulas of a yield spreadsheet, test it on a known case, spot the typical errors and produce three scenarios with a cautious client summary.

Topics covered

  • yield spreadsheet
  • rental investment simulation
  • checking AI output
  • scenarios

Where it fits

Model a reliable rental yield

How do I build, with AI, a yield model I can actually use to make decisions?

Lessons in this module

  1. Master the indicators before handing them to AI
  2. Have AI build a yield spreadsheet, then check it (this lesson)
  3. Check tax and regulations without delegating the advice

What you will learn in the course

This lesson is part of the course AI for real estate professionals (France)

  • Identify the tasks in your work to hand to AI and the points where human checking is mandatory.
  • Prepare client data in line with the GDPR before any AI processing (minimize, pseudonymize or anonymize, choose the tool and plan).
  • Build a rental yield spreadsheet with AI (gross yield, net yield, cash flow, three scenarios) and check its formulas against a case worked out by hand.
  • Check a tax or regulatory claim produced by AI against a dated official source, and recognize when to consult a professional.
  • Write a listing with AI that includes the mandatory notices and no unverifiable claim.
  • Produce a reasoned valuation range from DVF comparables given to the AI, and qualify a lead with an explicit grid, explaining the limits of each result.
  • Specify a field prospecting app, validate it in a spreadsheet, then prototype it without code, listing what is missing for production use.

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