Smarter Tomorrow: How AI Can Drive Change and Correct Bias In Post-COVID Real Estate

artificial intelligence applied

As the real estate industry absorbs the volatility of the pandemic economy, novel opportunities have presented themselves alongside never-before-seen challenges. In both cases, technology has been at the core of our response. Investors are leveraging data to understand consumer shifts and plan for future patterns. Real estate professionals are relying on digital platforms to interact with leads and facilitate showings. And almost all of us are looking toward artificial intelligence as we try our best to make informed preparations for the coming year.

A long-time four-letter-word in the industry, tech has slowly moved to the forefront of real estate. Every day, I’m talking with dynamic startup founders who are starting to leverage tech to bring innovation to this traditionally very stable (but very inert) sector. For those deeply dug in to their old ways, artificial intelligence can be a source of unease and consternation.

First, a little background. Artificial intelligence, commonly referred to as AI, is a type of smart technology that’s able to interpret a wealth of data and employ advanced algorithmic processes, combined with predictive analytics, to offer data-based, future-oriented estimations and solutions. Machine learning (ML) is a branch of AI that can go beyond patterned analysis to identify new and crucial relationships in our data, recommend a course of action, and take the next autonomous step. As you can image, the applications are almost endless.

Of course, great power brings great responsibility. The unease around artificial intelligence stems mainly from dystopian imaginings—an army of machines acting autonomously to take over the workforce and replace all human labor. But in our shared reality, AI is far from an industry threat. In fact, with the amount of troubleshooting and technological improvement in recent years, AI has the power to spearhead real estate’s recovery, to create new jobs and support growth in the post-COVID world.

Over all, I’m incredibly excited to watch AI take its rightful place in the FinTech and PropTech space, and I’m confident it will be a propelling force that will spearhead our recovery. Below are some direct applications I find particularly promising.

Directional Leads And An Improved Behind-The-Scenes

Consumer needs are completely in flux, and we’ve lost (for now) all organizing principles of normal market demand. Families used to want to live close to schools and not far from the office. Offices wanted to be close enough to the amenities of a city. Brick and mortar spaces were looking for optimal foot traffic. All of that, at least for the short-term future, has changed.

AI can help real estate agents identify their leads in the midst of all that market chaos and confusion. With minimal resource spend, AI can

understand the nature of a lead. Through deep learning, language processing, and behavioral recognition, it can differentiate a recreational Zillow-browser from a serious buyer ready to take the next step. Agents can prequalify their leads to match their asset class or budget range, and the machine can flag them when they have a customer in the queue.

AI can help real estate agents identify their leads in the midst of all that market chaos and confusion. With minimal resource spend, AI can understand the nature of a lead. Through deep learning, language processing, and behavioral recognition, it can differentiate a recreational Zillow-browser from a serious buyer ready to take the next step. Agents can prequalify their leads to match their asset class or budget range, and the machine can flag them when they have a customer in the queue.

AI assistant

This kind of match-making capacity also benefits the buyer, who will have a higher likelihood of finding a successful agent pairing. In fact, AI stands to improve many aspects of the prospective buyer experience. Machines can better handle daily inquiries and back-end tasks, taking repetitive and mindless to-dos off the professional’s shoulders. The professional is then left with more time to engage with the client and participate in the more complex end of customer relations. Done correctly, AI can minimize backend error, streamline day-to-day operations, and make for a much closer client experience.

Better Valuations — For People and For Property

Valuation accuracy is critical to real estate investing and an incredibly valuable prospect of AI. Surprisingly, it’s one that I don’t hear talked about as often as I believe it should be. One of the best applications of the predictive capacities of AI is to improve our accuracy regarding the assessment of property values, and how they’ll change in the short and medium term.

AI can produce valuation models that pull data from public records, school districts, transportation density, and a wealth of other sources that make it far more accurate than we could ever hope to be.

This same principle applies in the lending space, and it’s one of the most heartening promises of artificial intelligence in my opinion. Professionals in the default servicing and lending space can use AI and ML to accurately assess a borrower and find them the best lending arrangement. It can mine data from a myriad of sources without any paperwork headaches. It can learn as it goes, understanding which data points help to best asses a borrower’s financial profile, and which decisions lead to accuracy.

This is incredibly promising as we strive to eradicate human error and deliver a completely unbiased assessment of an applicant’s creditworthiness. It’s these kinds of examples that show us how tech can make us fairer, more right, and more human, and it’s a step forward we could have benefited from long ago.

In short, I’m incredibly hopeful for the growth that’s to come in the real estate sector. The successful integration of AI will accelerate real estate’s recovery and elevate all operations in the post-pandemic age. Most importantly, I look forward to AI as a way to deepen human connection and irradicate bias in the lending industry. I believe we’re witnessing the beginning of a very good thing.