How artificial intelligence could change the way you buy or sell your next house

By Aarthi Swaminathan

Will AI help people navigate an increasingly difficult housing market?

With temperatures running into the 80s in her suburban neighborhood in Dayton, Ohio, Katie Hill decided during the height of the pandemic that she wanted a house with a swimming pool. Hill's two kids - going stir-crazy during the government-mandated shutdown to stop the spread of the coronavirus - needed a respite, and public pools were off-limits.

Hill, 45, owned her four-bedroom house, which had appreciated in value between 2012, when she bought it, and 2020, and had a mortgage rate of around 4%. She decided to take action by walking up to her neighbor across the street, a man close to retirement, to ask if he had an interest in selling his home - which had a pool.

At this point, the housing market was going bananas. Bidding wars, soaring home prices and mass investor purchases all compounded into a pandemic-era buying frenzy. Hill's neighbor said he was keen, and was already thinking about selling - but wanted to wait until he retired, if she was willing to wait.

"That experience got me thinking that people should be having more conversations about their property plans," Hill told MarketWatch in an interview. "If we understand what people's plans are, then that's where there's an opportunity."

The encounter planted a seed in Hill's brain that then evolved into her setting up a new company, which she called Unlisted - a software platform that is driven by artificial intelligence to connect owners of off-market properties with people interested in buying them.

To be sure, her strategy of knocking on her neighbor's door to ask if he was selling was something real-estate agents and investors have done since time immemorial. But Hill believed that artificial intelligence and machine learning could offer significant value to the process of buying and selling homes, particularly homes that are off the market.

Hill is far from the only person thinking about how AI could impact real estate. From trying to predict when and where people are likely to sell their homes, to what kind of outreach would be most effective, real-estate investors - who buy and sell houses relatively frequently - have already begun to use technology to make smarter bets.

But a far more important application of this technology could come when people start using AI for transactions involving homes in which they reside. That technology could potentially upend the traditional method of listing and selling homes and even the business model of brokers, whose business is already under assault due to changes to traditionally lucrative commission rules. At a time when the American housing market is grappling with historically low inventory, the ability to accurately predict when a homeowner will sell is prized intelligence. With the housing market feeling increasingly dysfunctional, using AI to make better residential real-estate decisions could end up being one of the Best New Ideas in Money.

"In the past couple of years, we've seen 300% growth just with our AI product," said Greg Clement, CEO of Realeflow, an AI-driven software provider for people in the residential real-estate market.

There are different types of AI, but in the real-estate industry, the ability of AI to use existing data to predict patterns over time and provide forecasts - as well as generative AI's ability to create images, text, video and more based on user prompts - has unleashed a realm of possibilities to shake up an industry that has generally been a slow adopter to technology.

Aside from data points such as where a house is located and the kind of income its homeowners make, Realeflow also includes variables such as what kind of magazines the homeowners subscribe to, the age of the children in the house and even the type of car they drive, as a measure to predict the likelihood of them selling their home. "We knew that certain things trigger people wanting to sell property," Clement said.

There can be no doubt that there is plenty of AI hype, and the issues facing the American residential real-estate market appear to be structural and enduring. "AI goes in waves, and we're kind of at a teenage phase of generative AI where we're like, 'This is really cool ... but none of us are using it in every facet of daily life,'" Nicholas Stevens, vice president of product, artificial intelligence at real-estate company Zillow Group (ZG), told MarketWatch.

But companies such as Zillow are starting to use AI in different ways, like detecting users' behavior to help them search and identify more relevant home listings.

The problem

The housing market today faces a unique problem: With a so-called lock-in effect, homeowners with ultra-low mortgage rates are holding out on listing their homes. Consequently, inventory is low, as seen in the chart above.

The number of homes available for sale is measured by a metric referred to as months' supply by the real-estate industry. Unsold inventory in March was at a 3.2-month supply, according to data from the National Association of Realtors, which reveals how few home listings currently exist. A more balanced market is considered to be one where there's 5 to 7 months of supply.

The lack of home listings is pressuring home prices upwards. In March, the median price of a resale home was $393,500, while the median sales price of a newly built home was $430,700.

Home prices haven't significantly dropped in the last year, despite mortgage rates going up as high as 8% and settling around 7% for the time being, which has eroded what buyers can afford. Home prices are also rising faster than wages, the NAR noted.

"Home buyers are frustrated," Lawrence Yun, chief economist at the NAR, said on a call with reporters in March. Even if buyers can afford to buy a home, they face bidding wars given the stubbornly low inventory levels, he added.

With this backdrop, the technology that comes with artificial intelligence offers an edge for both home buyers and sellers.

With the ability to perform routine tasks - from applying for a mortgage to digesting millions of home listings to find something attuned to one's interests - the technology could offer not only convenience, but also speed and savings, potentially.

Feeding home buyers information based on preference

The platforms that some companies currently offer provide a glimpse of what could be possible.

Consider Realeflow: The startup offers a comprehensive approach for a fee of up to $400. Investors on the platform can identify which neighborhoods and which homes out 130 million in the U.S. have the highest likelihood of being sold, and also recommends the best times to send mailers or targeted social-media advertisements to those groups.

At another company, New Western - a real-estate marketplace that lists properties geared at fix-and-flip real-estate investors - artificial intelligence plays a role in curating listings for the website's 200,000 users. "In any given city, there's not more than 10 or 12 properties in a day on that marketplace, because they sell in a day," Kurt Carlton, co-founder and president of New Western, told MarketWatch.

As each local investor has a unique set of interests, the firm uses artificial intelligence and machine learning to monitor their behavior on the platform, and gives them a notification, at speed, when something that fits their criteria becomes available, Carlton explained.

"That's very important because these properties are generally available on our platform for [approximately] two hours," he added. "[Investors] can really focus on three or four properties a month, instead of having to spend an hour going through four or five properties."

That level of precision is slowly becoming more accessible to the public.

Zillow - one of the most well-known real-estate companies in America, and famous for its publicly available home listings and its proprietary Zestimate home-value estimator - is also embracing artificial intelligence.

For instance, when searching for homes on Zillow, instead of plugging in one's budget, how many bedrooms they would like and checking off a series of boxes about their preferences on the website, users can now type in what they want in a more natural language that the company's artificial-intelligence models can respond to, allowing them to find listings more suited to their taste, Stevens, Zillow's AI chief, said.

In other words, the new technology can be used to feed users content and ideas based on their preferences - whether they're looking for ranch houses, two-car garages or a house's proximity to coffee shops.

"With generative AI, we're able to extract information about the images - so if you love that big kitchen, [or] a big backyard, you don't have to tell us anymore," Stevens added. "We can see that based on your interactions and then use that in search ranking behind the scenes."

Current homeowners aren't left out. AI is also improving how home values are being measured via the Zestimate, Stevens noted. Instead of simply basing valuations on static data such as square footage, location or the number of bedrooms or bathrooms, so-called unstructured data enters the fray, based on what the listing images look like and how the listing agent has described them.

'The models don't get far without great data'

But getting to a point where the real-estate industry has at last begun to embrace AI was not easy. Experts who spoke with MarketWatch stressed the difficulty in processing highly disconnected data sets together, a necessity when trying to use artificial intelligence.

"The data is more nuanced in real estate," Zillow's Stevens said. "The models don't get far without great data." Location data, mortgage information, property taxes, flood risk, neighborhood desirability, projected rental income, comparable values - the list goes on.

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05-25-24 1119ET

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