AI in Real Estate : The Art of the possible
More about Artificial Intelligence at work in the real estate industry and its game changing ability.
AI
Artificial intelligence was subjected to a great deal of fantasy and imaginative hype in the 60’s, and was much talked about in the 80’s in both industry and academic circles. It is only in the last decade and counting that AI has emerged as a decisive factor in many industries as widely divergent as robotics and real estate. While we can understand or rather gauge the importance that machine learning may have to robots, it may not be as apparent in real estate. Part of it is due to the fact that we need to take a good and long look at what AI can actually for an industry that is concerned with buying and selling property (to put it loosely).
Where is artificial intelligence headed at the moment? Well, for starters, it is no longer confined to beating humans at a game of chess or Go. That happened yesterday. Machine Learning, or Deep Learning has come a long way since. Today, Artificial Intelligence can study algorithms in detail while analyzing mountains of data and then make very accurate estimations and predictions. Machine Learning happens to be the most exciting field to be in, and we see new technologies appearing almost every week. Compare that with a generation ago, when people were content with slow and staid changes, and revolutionary breakthroughs were few and far between. We live in heady times today, and new applications and opportunities make it a very exciting time to be alive indeed.
AI in Real Estate
Artificial Intelligence, Natural Language Processing, Machine Learning, and Natural Language Generation are familiar technologies with the Real Estate Industry as of today. They are however, still in nascent stages in the Real Estate industry, but what they have made possible and the promise they holds for the future is really mindboggling.
What is already possible?
It makes sense to leverage AI in Real Estate because the current market in 2018 is very much a seller’s market. Matching a potential customer to his/her preferred location and building is one of the things that AI is assisting brokers with. Let us look at what is already a reality with present Artificial Intelligence at hand;
- AI can accurately predict the demand of a certain listing in the market, factoring in the location and salient features. It can also predict correct house price when it takes into reckoning the location of the house, its age, the area available, number of rooms, overall energy efficiency, as well as the quality of life in that particular area. For the last one, AI factors in the type of building, the kind of transport being used and also commute times.
- Scanning real estate documents is a peach, with AI quickly identifying key terms as well as red flags. Using NLP or Natural Language Processing for scanning, there is very little need for an individual to oversee things, as long as relevant data keeps pouring in.
- Long Term Value of a new listing can be predicted with unerring accuracy and at par with human evaluations.
- AI can also predict the probable time that a customer will use a particular listing before moving on. Call it the Customer Attention Span
- AI is great with Image Recognition, being able to scan millions of images as to come up with similar listings in order for the paying customer to compare.
- Classification of user needs is possible if there are sensors in place to gather data on user behavior. Exclusive aspects of a property can be highlighted using NLP.
- With Machine Learning it is possible to analyze previous interactions between customers and brokers, as well as the deals that were hammered out. This helps in better future property evaluation and assigning offers.
- By analyzing historical income data, it is now possible to automate the process of underwriting in commercial mortgage thanks to Machine Learning.
- Machine Learning and AI can be harnessed to list out commercial properties in different areas.
- Machine Learning has great scope in predicting prepayments, especially at a time when there is increasing refinancing and defaults.
- Machine Learning is a proven tool in gauging the approximate value of different residences. For this, it needs a large quantity of data culled from different sources like the census data, social media, public records, and also stores.
- By analyzing the demographics, income scale, life events and purchasing behavior of a seller, Machine Learning is able to predict the likelihood that a property owner has of letting go of his property at any given time.
- Bleeding edge technology involving Machine learning, called ER Trees, can now be harnessed to identify markets and put them in order of relevance, based on their past performance, and also accounting for seasons and market cycles. It can also inform you of the best possible time to send an email or call a potential customer.
- A lot of marketing effort, time and money can be otherwise utilized because Machine Learning now has the capability of pointing out the appropriate media by means of which a real estate agent can market a property.
- With a remarkably human approach, Machine Learning and Natural Language Processing can direct a broker as to what kind of language and tone is most likely to work with any specific customer.
- Historical sales records can be thoroughly analyzed to predict the time frame in which a property is likely to be sold. Property valuations are also possible today with AI.
- Chatbots are employed by many real estate agencies to sell properties, interact with customers and develop accurate customer profiles which help when a particular deal is on the cards.
- AI can now predict what manner of zoning developments are likely in a particular area.
- Potential buyers can be targeted by the way they click on advertisements. By analyzing Big Data, potential developments in a city can be ideated or predicted to an extent.
- With integration of the Internet of Things, it is very possible to improve upon automating buildings further according to resident behavior patterns.
What can be possible in the future?
Now, it is quite important that we do not go overboard in our enthusiasm with AI and keep a hold on reality. We have to understand that the developments above took many long days and months of dedicated efforts by talented and top notch professionals. The question is, how many real estate companies are willing to go out on an arm and leg to hire these professional development teams, who have much better paying jobs in other companies that are deeply reliant on AI, and which can afford the exorbitant salaries these professionals rightly command? The real estate industry needs visionary thinking to plow further into the possibilities and advantages that emerging AI and Deep Learning have to offer.
Building a human relation a broker and a client is still a top priority, because clients really do not want to do business with a machine, unless it’s an e-commerce store. And real estate has a long way to go before people start buying listings off the Internet, attractive as the proposal may sound. Talented salespeople are still the backbone of any real estate agency, and their expertise in sounding out the customer will take considerable time to be duplicated by AI. Machine Learning depends on large amounts of data and relevant algorithms in order to learn, and if the input is not relevant, the output would be irrelevant as well.
One advantage of AI is that the technology is always awake, round the clock, seven days a week. Big real estate agencies need to cash in on this advantage to improve Chatbots to the point of them passing the Turing Test with flying colors. For the uninitiated, acing the Turing Test is when a human interacts with AI and another human, and is unable to tell the difference between the two. This will definitely improve customer relations with the company, which is vital to increased and improved business.
Another area where AI can have a deep impact in the future is in 3-D visualizations of properties, where a potential customer can take walkthroughs through a home stage up, asking questions on anything and everything about the property. Deep Learning can definitely be harnessed to provide the customer with an immersive experience in a possible home within his/her budget.
It falls to the decision makers in taking the call of employing talented individuals at premium rates who can dedicate themselves to sharpening AI to the point that the transition from human to machine dependent brokering is virtually seamless and unhindered. Many start-ups have made considerable headway by investing in technology and it falls to the big players to do the same, because AI is only going to get bigger in the future. We do not see AI improvements slowing down anytime soon, and it would be best to get on to the bus while there are still some seats left, or risk missing out on these fabulous advances in technology.