Traces of automation can be found throughout the residential real estate market: listings, price estimates and home loans are available at the press of a button. In China, buyers can even consult robot Realtors.
Commercial real estate, on the other hand, with its higher stakes and more complex deals, has been less susceptible to digital disruption. However, firms are still turning to artificial intelligence for a tech edge.
Greystone is the latest real estate firm to dive into computer automation, partnering with Skyline AI, a New York- and Tel Aviv-based startup that specializes in data aggregation and benchmarking in the commercial investment market.
With Skyline AI’s assessment system and Greystone’s financial records as well as the machine learning software of Greystone Labs — the lender’s in-house tech department — the partnership aims to underwrite loans as much as 10 times faster and with more accuracy.
“Our collaboration with Skyline AI will allow us to combine our industry expertise in both lending and investment with their expertise in data science and artificial intelligence,” Zac Rosenberg, director of Greystone Labs, said. “Together we will push even further into leveraging artificial intelligence in our underwriting models to surface insights previously impossible to achieve.”
Savills Studley made a similar move last month by partnering with Leverton’s to develop a machine learning platform that can extract and digitally catalog information from leases and other paper documents.
Industry-wide, advisory firms and venture capitalists are investing billions of dollars into various real estate technologies, also known as proptech, according to a survey from the research firm IDC and the Canadian real estate advisory, Altus Group. During the past four years, $6.2 billion has made its way to proptech startups.
While much of this investment has gone to smart building innovations, blockchain systems and other technologies, artificial intelligence and machine learning are among the most highly touted types of proptech. Michael Crook, a senior vice president at Altus, said this is because AI is far-reaching but also somewhat nebulous.
“AI is what we call things that computers can’t do yet,” Crook said. “We thought we would have AI when computers could speak and now that that’s possible, we don’t talk about it as AI anymore. “We’re still early enough in the industry that it’s easy to stamp AI in your marketing packet without really having a lot to back it up,” he added.
As every other industry it touches, artificial intelligence also raises the question of human displacement in the real estate industry but Crook said it’s unlikely to put anyone in real estate out of work. Though AI could significantly reduce clerical work and document review, he said there will still be plenty of other work for his and other firms.
“In general, there’s plenty of room for those people to give up those jobs and do more value-add activities,” he said. “There’s going to be less work to be done but there are so many other things for people to do that I don’t think it’s really going to move the needle on employment.”
Altus’s survey of 400 commercial real estate executives showed a similar sentiment throughout the industry. Of those interviewed, only 28 percent believe AI would create major disruptive changes in commercial real estate and just 24 percent thought the same of big data and predictive analytics.
Roughly 40 percent of those surveyed felt AI and big data would have little to no impact on the way they conduct business. Meanwhile, 80 percent believe smart building technology will either result in significant cost savings or be an outright game changer.
Much like Zillow’s “Zestimate” in the residential field, Crook said commercial real estate companies are also developing valuation software that can analyze thousands of comps and generate price estimates.
However, these machine-generated figures can’t be taken alone and at face value, he said. Rather, these prices are paired with human analysis to add nuance and make sure there’s someone to “go after” should things not pan out.
AI could also be used to advise investors, Crook said, to help them make decisions about capital improvements.
“The idea is to tell [the program] what kind of property you own and it could tell you about ones that are similar but slightly more valuable after making a certain investment, like a lobby improvement,” he said. “That could let an owner know how much they stand to gain by making an additional investment into their property.”