Artificial intelligence is already powering a number of real estate technology tools, but it’s still an emerging technology that has an opportunity to change the industry, said David Conroy, director of emerging technology with the National Association of REALTORS®, during the Federal Technology Policy Committee meeting on Wednesday. AI is already being used to help increase home values, turn more potential buyers into homeowners, and even predict where clients may come from, speakers said during the virtual meeting at the REALTORS® Legislative Meetings & Trade Expo.
“I believe a tech revolution for the real estate industry will be driven by AI,” said Brian Lent, co-founder of Plunk, a mobile app that leverages artificial intelligence to forecast home valuation and remodeling projects in real time. Plunk was recently selected for the 2021 REACH program through Second Century Ventures, the strategic investment arm of the National Association of REALTORS® that focuses on mentoring startups in the real estate industry. “Data and advanced AI could be your secret weapon,” Lent said.
Speakers pointed to several uses of AI in real estate technology that either demonstrate problem-solving capabilities or display relationships between different data sets to help users make informed predictions.
Here are a few ways AI is being used in real estate now or in the near future:
Computer vision: With cameras and the appropriate AI, devices can recognize and label images. For example, these tools can identify elements within a photograph in a property listing, making features in the image searchable by viewers without having to enter written descriptions. (Read more: An MLS Is Using AI to Populate Fields Automatically) With Plunk, homeowners could snap a picture of their current kitchen and AI could be used to do an image analysis to rate its condition, appliances, fixtures, surfaces, and more. Then, owners can use a tool to compare kitchens with similar formats to theirs and view a cost range of potential upgrades to increase their home’s value.
Recommendation engines: This technology can be used to suggest different products or services based on data collected about your preferences. This has been used in online shopping experiences, where users will see recommended products based on previous products they have shown an interest in. Conroy said this is an area ripe for growth in real estate. For example, as potential buyers browse properties for sale online, AI could be used to offer up visually similar properties to consider. “This could improve the search process,” Conroy said. “This is an area in real estate, I believe, we’ll see very soon.”
Using predictive analytics to make new homeowners: The startup Landis is leveraging AI to make predictions on whether a renter could have the future financial means to purchase a home. If so, they’ll take so much faith in that AI prediction that they’ll buy a home for the consumer. Landis, also a 2021 REACH class participant, works with real estate professionals to provide a path to homeownership for clients who are struggling financially. The client may be unable to qualify for a mortgage due to a low credit score or need for a low down payment. The real estate professional can refer that buyer client to Landis, who will then review the person’s income and financials and use AI to predict whether they can be made mortgage-ready in the near future. If they can, Landis will provide them with a specified budget to shop for a home and then make a cash offer for the home on their behalf. (The real estate professional represents Landis as the buyer’s agent to earn a commission.) The buyer will then rent the home from Landis, and the firm will coach them on improving their finances so they can eventually qualify for a mortgage and buy the home from Landis for a prior agreed price. The majority of these buyers purchase the homes from Landis within a year, said Cyril Berdugo, co-founder of Landis. Landis is currently available in select markets.
Smarter CRMs: Predictive analytics from AI also could help accurately predict prospects who are most likely to soon buy or sell by analyzing public and private data (encompassing a range of data points such as changes in marital or mortgage status or even dumpster rentals) that can be used to predict mobility. For example, Coldwell Banker’s CBx Technology Suite is a platform for identifying seller leads and predicts where buyers are likely to come from using sales and demographic information, such as a new job or a new baby. Agents can use the predictions to try to help generate seller or buyer leads. (Read more: How a Franchise Giant Uses AI to Predict the Future)
Choosing properties for investment: AI could offer greater insight into residential and commercial properties for investors. For example, Reonomy uses AI to serve up property intelligence on commercial properties nationwide, allowing searches by asset types, square footage, building ownership, transaction history, tax assessment, opportunity zones, and more. Lent showed how Plunk also could be used to pinpoint properties, such as by displaying areas where values have seen rapid growth over the past year to help identify fixer-uppers that could make for strong buying opportunities.
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