The Future Impact of AI on the Real Estate Market

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Guest blogger Abhi Golhar shares his observations and thoughts about the present and future role of AI in real estate.

Artificial intelligence is proven to be one of the most major disruptors of the proptech transformation in real estate. This real estate sector is discovering how to handle the huge volumes of data that buildings create, as well as monitor specific KPIs to expedite operations and extrapolate important information, thanks to improvements in machine learning and the fast expansion of AI.

Artificial intelligence (AI) is a term that refers to a group of software programs that attempt to solve problems in a fashion that resembles human intelligence. Machine learning usually entails extensive data categorization and analytics by software applications, which enable computers to learn by recognizing complicated patterns in massive data sets.

In real estate, there are five ways AI is being employed. With this in mind, it’s critical to consider how artificial intelligence is influencing the changes in the real estate business. In fact, AI technologies have impacted practically every facet of the real estate industry in recent years. Here are a few instances of how AI is influencing your normal real estate transaction.

It aids in the production of leads for agents.

Most agents are aware that they will get a large number of non-serious website visits and prospective leads. After all, visiting a real estate site and wondering about buying a multimillion-dollar house is a typical activity these days.

Rather than the agent having to comb through all of their leads to determine which have the best chance of becoming a genuine client in the coming future, deep learning enables AI to evaluate leads appropriately.

Other websites use natural language processing tools to assist specialty agents in identifying their potential clientele. An agent who specializes in the high-end market, for example, might utilize this real estate tech to preapprove leads so that they don’t spend time looking for customers who can’t afford their offerings.

It’s changing the way people look for homes.

Technology has played a part in assisting purchasers in their house search since listings were made accessible online. While practically every house search engine enables real estate agents and potential buyers to filter a property search by the list of criteria such as the number of rooms and baths or geography, this strategy often provides everyone with many choices.

This is when the AI algorithm enters the picture. Many of today’s house search tools may utilize those search parameters to determine a user’s preferences and then choose homes based on that information. Most algorithms may then suggest alternative listings that would be a suitable match for the user’s search criteria, with the best-fitting items appearing first in the user’s search results.

It’s about making transactions more efficient.

AI may also make it simpler for the agent to handle their real estate firm on the back end of the agreement. Various customer relationship management solutions, for example, use machine learning to generate automated reports and auto-fillable information.

Not only does this lessen the length of time an agent has spent in front of a desktop doing office activities, but it also tends to minimize the number of mistakes by removing the human element from data entering.

It simplifies the process of determining the value of a property.

Furthermore, real estate brokers have come to depend on AI’s capacity to “predict” the future as one of its most important qualities. This is very useful for determining asset and rental values.

In this case, an AI software’s automated valuation model may collect information such as public records, transit alternatives, crime rate statistics in the region, and local school ratings in addition to creating a value analysis for a specific property.

On the one hand, during the coronavirus epidemic where everything was shut and everybody was to maintain social distancing to avoid the spread of infection, this type of desktop evaluation proved very valuable. Beyond that, it will almost certainly continue to be a helpful tool for real estate brokers when creating comparative market analysis, and for investors when considering whether to add additional properties to their portfolios.

It’s altering the way we think about loans.

Finally, machine learning has influenced the mortgage business. As every agent or investor understands, underwriters sift through all of the information gathered in order to assess whether to lend to a potential borrower.

However, before the paperwork is given over to the underwriters, the process of desktop insurance employs AI technology to analyze those papers and make an initial assessment. While desktop insurance does not usually completely replace the human portion of this process, it does greatly speed it up.

AI that simplifies the current loan process.

Large lenders employ AI to cut down on underwriting costs and delays, resulting in higher profits per loan. Some IT businesses have now taken things a step further by employing AI to automate the whole lending procedure. Fans of this technology claim that it reduces prejudice and results in better loans.

Upstart promises to employ AI to automate the whole loan process, from application to final decision. Variables such as educational degrees, the field of study, and careers are used by machine learning algorithms.

Finding and delighting consumers via artificial intelligence.

Amazon, the e-commerce titan, lends billions of dollars to small firms who resell on its site. Based on their stock turnover and revenue, AI is being used to identify debtors who have low credit risks. Amazon uses AI exclusively, so no humans are engaged in any way, even filling out applications, and it makes unsolicited loans on “take it or leave it” conditions.

AI is largely employed in the sphere of customer service for things like chatbots. Companies assist customers with their complete financial picture, such as improving take-home income, lowering spending, and eliminating debt. Customers seem to value the service, making them more dependable borrowers in the future.

Using artificial intelligence in hard money lending.

It’s easy to believe that hard money loans are easier to get since the lenders work with significantly fewer applicants than banks and have assets as security. These lenders don’t require AI.

However, AI might be used to discover new prospective borrowers, improve the loan process, detect dangers and possibilities, and more. You don’t have to recruit a team of programmers and data scientists; some AI businesses provide software as a subscription.

Some hard money lenders used to argue that they didn’t require the internet to do their business. Few people nowadays would be able to get something done without it. This is how AI in our sector will progress: from a novelty to a necessary tool that allows you to earn more. From filling all the documents to completing the whole procedure, buyers and lenders will rely on AI in the future.

What are the benefits of using AI in real estate investing?

Now that you have a better understanding of how AI learning may improve the real estate market as a whole, it’s time to look at how investors might profit from this technology.

To that purpose, we’ve included a few samples below. Read through them to see whether introducing machine learning to your company is something you should think about.

Obtain assistance with decision-making.

This was briefly discussed earlier, but it’s so crucial that it’s worth repeating. In essence, some AI applications use predictive analytics to provide more information about a property’s present or future value.

This knowledge is priceless for an investor. For one thing, it might assist you in determining if a home fulfills your criteria before making an offer. For instance, it could be able to predict how much money you’ll make when it’s time to employ your exit plan.

Get a competitive advantage

Nevertheless, leveraging predictive analytics on your side can benefit you in more ways than one. It will also assist you to get an advantage over your competitors. Simply said, if an AI tool can assist you in obtaining a more accurate sense of a property’s value, it may also assist you in determining what to offer.

In today’s real estate market, when there are often several offers on the table, you’ll be able to move ahead by making more knowledgeable bids.

The Future Of Artificial Intelligence In Real Estate

The ability of AI to assist real estate organizations in a variety of ways is game-changing. Additional case studies, such as other AI divisions, will be emphasized by decision-makers in order to enhance the real estate business. Clients and owners will become more productive if businesses rapidly learn how to use data science to their businesses.

Embracing AI in real estate is a continuous process rather than a one-time event; organizations should define long-term objectives and utilize AI technologies to get there faster and with more clarity.

Although AI will not be able to completely replace humans, it will play an essential role in the future. People don’t purchase houses; they buy psychological and emotional choices that allow them to feel at ease in their own homes.

Emotional AI should be created in the future to study human emotions in detail and to see the emotional consequences of domestic elections.

Final Thought

Artificial intelligence and machine learning systems seem to be becoming smarter by the day. While it’s impossible to predict where technology will lead us towards tomorrow, one thing is certain: it can already be utilized to assist agents and investors.

With that in mind, consider this guide to artificial intelligence in real estate. Now that you have this expertise, you should be able to take your real estate firm to the next level.


Abhi Golhar is a nationally syndicated media host, entrepreneur, and sought-after speaker with a large national following and wealth of resources to share in the Real Estate investment industry. He has built and manages a sizable, profitable investment portfolio across the Southeast US, with expertise in benchmark markets. You can contact Abhi at