How AI is Quietly Revolutionizing Homebuying

Artificial intelligence (AI) is quietly infiltrating the real estate industry — without looking like a futuristic takeover but rather a boon for buyers and sellers.

Mortgage lenders, realtors, title companies, property appraisers and consumers use AI for a wide variety of purposes, including application automation, expediting processes, chatbots on real estate sites and automated valuations models, or AVMs, to name a few.

“AI can benefit real estate industry participants in many ways. An example is the use of machine learning to link potential buyers with more relevant properties, creating an enhanced real estate transaction (more timely and focused),” says John D’Angelo, managing director at Deloitte Consulting LLP. “This can also make it easier for buyers and sellers to receive more personalized offerings based on their preferences. In addition, AI can reduce the transaction costs for buyers and sellers by shortening the transaction cycle.”

Communication between buyers and sellers can be augmented with AI, as well, says Adrian Fisher, CEO at Property Simple. This kind of technology is a useful tool for real estate agents who want to provide fast responses to their clients, without spending resources on more staff. These cost-savings can be passed on to consumers.

“Chatbots can already answer simple queries to help potential buyers find their next home. If they’re unable to provide an answer, these bots can notify human agents to take over and offer a better, more customized response,” Fisher says. “As machine learning advances, chatbots will become smarter. In the future, they’ll be able to answer complex search queries proficiently, including those through voice technology.”


The enormous amount of data available, due in part to the digitization of information — makes AI an increasingly important tool in parsing that data in a way that’s meaningful to buyers and sellers.

Ramneek Gupta, managing director and co-head of venture investing at Citi Ventures, cites two companies that are using AI to dive into big data for a more efficient and results-driven experience.

Reonomy, for instance, uses AI and machine learning to automate the aggregation, clean up and feature extraction from large amounts of alternative data (information used in the investment process) on more than 50 million commercial real estate properties.

“This enables both buyers and sellers to make better sourcing, pricing and buying decisions,” says Gupta. “Another example is Homelight, a company that uses AI and machine learning to improve its pricing algorithms. Homelight leverages historical data and input from homeowners and agents to come up with accurate home price estimates.”


There are limitations to AI, says Peggy Zabakolas, Esq., real estate broker for Nest Seekers International. Already, most homebuyers use AI to look for a home online, loading their specifications to filter properties that meet those requirements.

But when it’s time to buy, AI is not equipped to understand the nuances of purchasing the home, which includes a detailed understanding of the market and negotiating, Zabakolas adds. She also points out that AI might not have information on all the properties available, including those that might be word-of-mouth sales.

“Buyers are becoming more and more knowledgeable, which is wonderful, but when I’m going to spend millions or hundreds of thousands of dollars on a property, I want to work with a human that has expertise in negotiating and getting a deal done,” Zabakolas says. “Also, agents may know of properties off-market that AI may not necessarily have access to.”


Although AI is transforming how companies do business, it’s still in its infancy. In fact, there are major hurdles technologists and policymakers have to overcome to increase AI security and eradicate bias.

Recently, at the World Economic Forum in Davos, IBM Policy Lab co-directors Ryan Hagemann and Jean-Marc Leclerc urged global regulation of artificial intelligence based on accountability, transparency, fairness and security. Their argument is that technology relies on data with “baked-in” bias, which includes discrimination against women, minorities, the disabled, older Americans and others.

“I see an abundance of technology but a shortage of actionable policy ideas to ensure we protect people while allowing innovation to thrive,” Christopher Padilla, vice president of government & regulatory affairs at IBM, said in a statement. “The IBM Policy Lab will set a new standard for how business can partner with governments and other stakeholders to help serve the interests of society.”

A report issued by the FDIC in February last year showed that both face-to-face and FinTech lenders charged Latinx and African-American borrowers 6- to 9-basis points more in interest for purchase mortgages, which is “consistent with the extraction of monopoly rents in weaker competitive environments and from profiling borrowers on shopping behavior.”

In total, Latinx and African-Americans pay some $750 million per year in extra mortgage interest, according to the report. This is where policy, like what IBM proposes, becomes critical moving forward in our dependency on and use of AI.


The bottom line, for consumers, is to do their due diligence when shopping for or selling a home. Leveraging online tools, like rate comparison tables, is a great way to use AI to find the most competitive rates. Although AI is a powerful tool, it can also pose security threats, so practice caution when you’re using things like electronic documents, online portals and other AI-powered technology.

Make sure you have a clear understanding of security protocols in place when you send and receive documents via your lender. For example, some buyers have become victims of escrow wire fraud because they received an email from what looked like their bank asking to wire their escrow money, when in fact it was a scam artist. The unfortunate reality is that most victims of escrow wire fraud won’t recover their funds.

Finally, if you’re asked to enter personal information online, like your social security number, make sure the request comes directly from your lender. Double- and triple-check online transactions to ensure you don’t fall prey to a scam, virus or security pitfall.


(Article written by Natalie Campisi)