“So many areas in real estate stand to benefit from artificial intelligence in the next five years”
Taylor Wescoatt, Founder, Concrete VC
5 December 2017
So, what’s all this talk about artificial intelligence (AI) in the real estate sector? What will it do? What human tasks will it replace? And is it coming before or after I retire?
We all recognise that the real estate sector is often a late adopter with new technology, but that’s not necessarily always a disadvantage. In fact, it means that these technologies are more mature and stable, so they can reliably deliver value.
AI is already at this stage of maturity. We see it at work every day in our Amazon recommendations, our Google search results and our Facebook ads, and we hear it when we talk to Siri. So why should we not start to feel its effects in real estate?
AI isn’t some futuristic robot; it’s just a term for a human-trained decision-making process executed by computers using big data sets. Imagine a partner and bunch of associates locked in a room, given lots of time and a really big stack of files. AI’s goal is to produce a similar output. Perhaps this is a simplistic comparison, but I want you to recognise that it’s just another step in the evolution of doing business better and faster.
As an early stage tech investor, it’s my job to spot the opportunities that AI represents, so here are just three examples of how it’s making an impact on the sector.
First, there’s valuations and the forecasting of asset values 12, 18 or 24 months out. Already the radiology sector has taken a great leap forward by partnering AI image analyses with human insights to do the job cheaper, faster and more accurately, and companies like GeoPhy, HouseCanary and Proportunity are working to enable this for the world of real estate valuation.
Another example is lease extraction. Traditionally this is a resource-intensive, time-consuming and errorprone human process. But AI has enabled some large brokers to dramatically improve accuracy and reduce costs by using automation to pull out key clauses and terms, while kicking targeted areas of concern up the chain for human evaluation. Companies like Leverton, Beagle and Kira are all making inroads in this area.
And finally, predictive maintenance – where realtime usage data gathered by sensors allows maintenance resources to be allocated precisely where and when they are needed – is another exciting opportunity. It’s already a big success in the energy and automotive sectors, and it would be foolish to bet against it having a similar impact in the running of built assets. Disruptive Technologies, Ravti, OpenSensors and Demand Logic are making early inroads in the application of this thinking to the real estate sector.
So many areas in real estate stand to benefit from AI in the next five years and beyond: sensing and predicting customer demand patterns, improving construction efficiency, and generally being able to choose and sweat built assets better.
Where the Amazons, Googles and Facebooks of the world have set the standard, the opportunity for real estate players is there for the taking.
Make sure you’re on the right side of history, and embrace it sooner rather than later.
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