A version of this article first appeared in the CNBC Property Play newsletter with Diana Olick. Property Play covers new and evolving opportunities for the real estate investor, from individuals to venture capitalists, private equity funds, family offices, institutional investors and large public companies. Sign up to receive future editions, straight to your inbox. A home is only worth what someone is willing to pay for it. That is probably the only dependable truth when it comes to putting a price tag on a property. Enter artificial intelligence. As with everything on the planet, AI is disrupting real estate. In March, celebrity real estate CEO Ryan Serhant, of his namesake company, posted a video on Instagram titled, “ChatGPT just blew up my $50M deal.” In the post, he explained how he had brokered a deal on the property, but, “at the last minute the seller uses ChatGPT, asks it, ‘Should I sell at this price?’ And maybe because of how he asked, whatnot, ChatGPT basically told him no, you should not sell at that price, it’s worth more.” Then, he said, the buyer did the same thing, asking the AI tool from OpenAI if he was overpaying, and ChatGPT told him that, yes, he was paying too much. “It gave him comparables that showed why, without context and without actually understanding the property,” Serhant said. Serhant’s post has more than 3 million views. He was able to salvage the deal, he said in a subsequent post, by explaining to both the buyer and seller the following about AI: “It doesn’t know the future, it can’t predict the future. It doesn’t know intentions, doesn’t know emotions, doesn’t know what buyers are circling, doesn’t know off-market comparables, doesn’t understand, fully, replacement costs, and doesn’t actually optimize for the deal,” he said. “AI can model a market. It can’t model a deal.” Serhant has said he does believe AI is a critical tool for real estate agents and even launched his own AI-powered workflow automation platform and operating system, called S.MPLE, which he talked about recently on the Property Play podcast. And he’s not alone. For most real estate professionals, the data aggregation capabilities of AI can certainly enhance their expertise, according to Kamini Lane, CEO of Coldwell Banker Realty. “Market analysis, comparative analysis, those are key tools in a real estate agent’s toolbox. But the important thing is that those are starting points for an agent to then apply their judgment, their expertise, their nuanced understanding of the real estate market, to either validate or enhance the recommendation that any data tool would provide,” she said. Lane said her agents are seeing more and more clients — both buyers and sellers — look to sources like Anthropic’s Claude and OpenAI’s ChatGPT to price their homes or calculate offers. Like Serhant, she warned of how these generalized large language models miss the nuances of a home, a neighborhood and a client. “One of the most important things that agents can see, that ChatGPT, or any other AI tool is not going to know, is [what’s] up and coming. So neighborhoods that are up and coming, design features that are up and coming,” she said. “Anecdotal data that agents are aggregating through their conversations, that is something that no AI tool is ever going to be able to aggregate in the same way that a real estate professional can.” Zillow, one could argue, was the original AI price model for residential real estate. It launched its so-called Zestimate feature back in 2006, alongside the launch of its website. It recently launched “AI mode,” designed to guide homebuyers through their search by learning their specific needs. It then enables homebuyers to have a more personalized conversation with the Zestimate. “AI guidance for consumers needs to be connected to real context, real data, real ability to take action,” said Nicholas Stevens, vice president of product and AI at Zillow. “Then that AI guidance needs to be deeply connected to what a real estate agent is attempting to do. That’s the difference between what we’re doing at Zillow versus like a third-party, generic experience.” Agents have to upload in-depth floor plans and 3D visual captures of the entire home and surrounding lot with every possible piece of information. Then, in AI mode, Zillow gives advice to the buyer on what might be a good offer. “It actually sees a remodeled kitchen. It actually sees upgrades in the house, and that’s useful, both for buyers but also homeowners thinking about selling or remodeling as well,” said Stevens. Zillow’s AI feature is now primarily for buyers, but Stevens said the company will roll out a tool for sellers as well. It still raises accuracy questions, however, about the AI itself as it tries to understand its human users. Coldwell Banker’s Lane said she worries that for both buyers and sellers, AI will not be able to pick up on what they might need compared with what they say they want. It might also not be inclined to offer the often hard-to-hear advice that a human agent has to. “Artificial intelligence is trained to be sycophantic, it’s trained to give you the answers that you want, so that you will continue to engage, and so AI is more likely to give you the price that you want versus the price at which a home is going to sell for,” said Lane.
Property Play: How AI may be messing with home prices
