So you want to be in PropTech?

How to Ideate a PropTech Business using Generative AI

PropTech VC PI Labs released a report last week about ‘AI for a Greener Built World’ titled ‘Sustainably Intelligent’.

In it they broke down environmental use cases along the real estate value chain. In 7 Categories.

So I thought ‘how could AI help someone develop a business aimed at one of more of these defined use cases?’

I started with Category 1: Site Supply and Acquisition.

This listed six tasks required:

  • Localised environmental data and analysis

  • Identification and monitoring of biodiversity

  • Biodiversity management and intervention

  • Robotic insecticide alternatives

  • Soil quality and health analysis

  • Microclimate simulations

So for each of these I enlisted the help of Claude 3 Opus.

First off I defined to it what I meant by Generative and Predictive AI.

Then I asked the following questions, for each item:

  • Might this benefit from Generative AI?

  • Might this benefit from Predictive AI?

In every case there was a use for Generative and Predictive AI (this is not surprising with a GPT - a General Purpose Technology - they are pervasive)

So, then I needed to know:

  • What ‘Actions’ could Generative AI take?

  • What ‘Actions’ could Predictive AI take?

And

  • What inputs (data) would be required so that these ‘Actions’ could be undertaken?

  • What Data Sources are these inputs likely to come from?

Then finally I asked:

  • What technology stack would we need?

  • What would be the right evaluation metrics for this item?

  • What integration requirements, with other systems, would we need?

Having done this I needed all this information formatted as a table and available to be downloaded.

I then took this into Google Slides, and cleaned it up a bit before ending up with the table below.

You’ve now got a strong set of data to start thinking about your proposed PropTech business.

You can see how Generative and Predictive AI can be woven together to provide analytics and presentation/communication layers. You can see what value there is to create, what data sources you would require to make this happen, and the technological skills your team would need access to.

From this you should be able to ascertain whether 1) it’s possible 2) You could make it happen and 3) Does it look like there’s enough value there for all the work involved?

Don’t like this category? Then work your way through the other 6.

Then you will have covered off environmental use cases for AI along the real estate value chain!

Is it a GO?

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