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AI Is Slowly Streamlining the Apartment Renting Process

Shaking up the real estate market is no easy feat. It has been slow to adopt the kind of disruptive change that other industries have seen in the past decade. While Airbnb has redefined short term stays, the real estate industry still lacks the kind of tipping point that businesses like Uber or Netflix have ushered in to reinvent how we travel or watch entertainment. Real estate remains too siloed and entrenched in past habits. That lack of disruption is what makes the industry such an opportunity, but also so difficult to truly enact much-needed change. That missing factor is artificial intelligence. 

It’s difficult to remember what it was like renting an apartment before the internet. You’d have to flip to the back of actual newspapers and thumb through the pages of classified ads without any context about the rentals besides an address, cost per month, and number of available bedrooms. The digital age has made it easier, but the only real option for renters searching for apartments in huge markets like New York City no more than a decade ago was Craigslist. Fake photos, difficult-to-contact brokers, and deleted details offered their own challenges. They were as much of a gamble as newspaper listings. 

There are more renters now than at any time in the past 50 years, and an overwhelming majority of those renters are going online and using mobile devices to find places to call home. The fundamental disconnect between real estate and current technology still makes it a struggle to meet this generation’s tech-savvy real estate demands. 

Now more than ever, people are used to taking care of their needs instantly and on their own terms. Renters and landlords have to become more reliant on AI and automation to streamline the normally mundane and off-putting tasks of the rental process. By making the rental journey easier and more efficient, AI gives professionals and renters more opportunities while also allowing the real estate innovations to develop alongside other cutting edge industries. 

Almost everyone agrees that certain real estate rental rites of passage remain a distinct hassle. Yet this is an industry that generates over $278 billion as of June 2018, and it’s still stubbornly living in the past. AI’s continued integration into the real estate industry is poised to break out as a way to solve some of its biggest challenges, unlock key insights, and supply the kind of innovation that will change the future of the business — here’s how.

Finding the Perfect Place

The prospect of finding a new place might make shivers run down your spine. Not only do you have to worry about moving your stuff and coordinating eventual move-in dates, but finding a place that turns out to be somewhere you actually want to live is usually a crapshoot. Your prospects are at the whim of the market, and your insights into what’s available is limited to whatever you happen to find on any number of websites on a given afternoon. 

Right now, most platforms only allow users the versatility to compare areas, amenities, or prices much in the same way people log on to Kayak to compare flights. From a renter’s perspective it’s still limited to the here-and-now, and from a landlord’s perspective it doesn’t come close to giving them guaranteed rental security. It’s all too imprecise. 

Back in the day, real estate agents and brokers actively got to know their clients on a one-on-one salesperson basis to interpret pain points and to find out what details would go into their dream rental. Now, AI steps into that role to bridge the personalization gap for the digital age. 

Take, for example, how nearly 50 percent of streaming platform users admit that personalized recommendations on those services influence their streaming tendencies. And that’s just for people deciding how many episodes of Stranger Things to watch in the next few hours of their evening. Think about that kind of targeted personalization for how you spend the next few years of your life!

AI can be used to personalize every customer interaction in real estate as well, beyond what kind of building people are looking for, in what general neighborhood, and what amenities they want. Algorithms can learn from choices and surface the exact building, neighborhood, amenities, and more for each different user across dozens (even hundreds) of touch points. Instead of a guessing game for renters, aggregating will actively personalize the rental process to more rapidly find better rentals. 

AI-powered platforms will also begin to use this technology to streamline the rental process for users to take their next steps. Anybody who has gone through headache-inducing rental experiences knows that there needs to be a way to view properties that doesn’t involve a constant stream of phone calls, emails, shifting schedules to visit and view with a broker at a time that works for users and third parties, paying exorbitant fees, or putting far too much information into lengthy applications. 

New tech-driven platforms will take the industry from the face-to-face dark ages into the future by removing common pain points and injecting digital pathways. Renting will no longer be a hassle, it’ll be an opportunity to find the best place out there.  

AI algorithms don’t just benefit the renters either. These touch points can factor into the landlord and investor’s journey as well. Much in the same way that there’s a limited scope when searching for listings, there’s also an equally limited capacity to reach out to or figure out how to find people searching for properties. It’s no longer sufficient to simply put up a listing, or hope to stumble upon a prospective building investment. That kind of less-than-aggressive strategy will leave you with a lot of empty spaces, the wrong renters, and wasted money. 

There is now a necessary AI component needed to truly gauge current market trends to predict the next ones. 

AI can harness crucial market data to generate essential information on rent averages and fluctuations and occupancy rates in addition to painting a bigger picture on a given property’s proximity to schools, crime rates, transportation options, food and entertainment trends, and more. The same data can be used to predict which potential renters might fail credit checks, which are more apt to move out, and even where they’d be likely to move.     

The market over the past decade or so has demonstrated that people are owning less and renting more, indicating that they’re constantly on the move from lease-to-lease. From a landlord’s perspective — not to mention platforms that offer apartment and property listings —  this allows them to move beyond the crippling one-time-use potential for renters. It also ensures a constant stream of users.

The real estate industry has largely focused on the here-and-now without thinking about the future. Before it was all about surveying the trends after the fact to assess what might happen months from now. Instead, AI can be the deciding factor in those vastly important predictions. 

That kind of information can in turn be used by investors to track larger real estate market indicators. Pinpointing the latest zip code that could be turned from forgotten to an up-and-coming hip neighborhood all hinges on AI-powered predictable accuracy. This means investors will also be armed with a rapid understanding of soon-to-market opportunities aimed to beat the competition. It’s all about an unprecedented level of speed and accuracy that augments landlord and investor experiences. 

When it boils down to who gets who to sign on the dotted line, there will likely be some human interaction. What AI can do is leverage the unseen and unspoken parts of that equation for the better for all parties involved. AI is making the process less laborious, empowering insights with more than an experiential hunch, and giving professionals and renters a powerful decision-making tool. How each person uses that tool will change the industry as we know it.  

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