Even though the first artificial intelligence AI programs begin to emerge in the 1950s, this technology had been the exclusive realm of computer scientists and leading-edge researchers. Today, however, it seems like we can’t talk about any subject or field wherein AI applications are not being discussed for their growing influence.
That includes the real estate sector. Those who don’t well understand AI can’t imagine how “intelligent machines” can have anything to do with buying a selling property. However, AI is doing nothing less than “transforming the real estate industry,” said Tara Mastroeni, a real estate writer for top media venues like Forbes and Business Insider.
We’ll forgo a tutorial on what exactly AI is here so that we can go right to describing key areas where AI is being used in real estate today.
Helping Agents Get More Clients
Real estate agents spend hours sifting through hundreds of e-mail inquiries and evaluating scads of people who contact via their websites and social media presence. The vast majority of these people are “unqualified” prospects who are likely to bog a busy agent down by wasting their time with half-baked intentions.
Now AI apps can be applied to these thousands of data points to pinpoint which prospects have the highest potential to convert into profitable clients.
Transforming Home/Property Research
Once again, webpages have been revolutionary in helping people searching for property. They offer an embarrassment of riches to choose from in just hours. Getting the same amount of data took days or weeks before the web. However, now that websites have proliferated to an enormous degree, wading through all that data means navigating a bottomless quagmire of information.
Here again, it’s AI to the rescue. AI apps can sift through gigantic amounts of relevant data posted across the internet and winnow out key data points finely attuned to the need of the property searcher. It makes real estate commerce vastly more efficient across the board.
Easier Property Valuation
This is an area where the “predictive” capability of AI comes into play. For example, an AI-driven “valuation model” can gather data from public records, an area’s transportation infrastructure, school district ratings, crime rate statistics, and much more — and use all of that to quickly nail down a value for a property in that area.