Artificial intelligence has been revolutionizing a wide range of industries, from banking to healthcare. The real estate industry is no exception. Let’s see how AI is being used to transform the real estate industry.
Applications of AI in real estate
Lead generation and qualification
It can be quite a difficult task for real estate industry agents to generate good quality leads for their various properties. This can, more often than not, leave them investing an enormous chunk of their time engaging with prospects who just might not be convertible at all.
But AI can help them combat this issue. Zillow makes use of thousands of factors and hundreds of data points to distinguish between leads that actually have a serious buying or selling intent and other leads who aren’t too serious and may never end up converting. Zillow’s Zestimate algorithm can even find out what type of property the prospect is looking for.
Real estate companies can even use AI-powered chatbots to begin the interactions with their leads and determine which of them have actual buying intent. The chatbots can even ask qualifying questions and carry out lead scoring before passing the lead on to your real estate agents so as to not waste your agents’ time.
Real estate agencies can now make use of AI-driven consumer apps and chatbots to deliver highly customized and personalized content directly to their leads and prospects. There also are AI powered tools that design powerful property ads for a range of social media platforms and then crunch data to target these ads to the right prospects. These tools even offer you performance insights regarding clicks, views, and demographics in real-time.
Property analysis and future valuation
When you’re buying property as an investment, you’d want to buy low and sell high. But you’ll always find yourself wondering what’s the right price to buy the property right now so that you can sell it at a profit in the future. Conducting the valuation of a property and estimating it’s future market value is quite a tough job, one that is very easy for you to get wrong. The future price is dependent on several variables… and that’s the thing about variables, they can change at any point of time. This just means that a realtor might not be able to manually keep track of every tiny detail, but that’s where AI comes into the picture.
AI technologies can monitor all this data, crunch the numbers, and even run predictive analytics to help real estate agencies estimate the future value of the properties with a greater degree of accuracy. This even makes it possible for real estate companies to deliver more comprehensive information about a property to their clients.
These AI tools combine existing market data with public information including crime rates, means of transportation, sources of light, sound disturbance, schools, amenities, entertainment centers, purchasing trends, etc.
Search and recommendation engines
AI powered search and suggestion engines work in a fashion similar to other recommendation engines that you’ve interacted with before. Just like the Netflix recommendation engine takes the content that you like watching and suggests similar movies and shows that you would enjoy, an AI search and recommendation engine would evaluate your clients’ property preferences and list out the best options available to them. This makes it possible for you to speed up the property search process and enables your clients to find their dream property as quickly as possible.
Rental property management is no easy job. There’s a lot of effort involved, all the way from rental applications and transactions to generating lease agreements and disclosure statements. The good news is that you can use artificial intelligence systems to automate and streamline your property management processes.
These real estate AI systems can create documents automatically and even parse through property documents to pull data and store it in the system, while also scanning for errors like missing signatures, unfilled fields, etc.
AI systems can even tackle the task of accounting for your real estate business. They can keep records of rental transactions, payables, and receivables and can even update your tax payments.
Virtual tours are one of the newest and most powerful developments in the real estate world. This technology makes it possible for prospects to experience a 3D tour of the property from wherever they are. It essentially offers them a property viewing without needing them to actually visit the property themselves. This could allow clients to make a better decision about whether they would like to invest the time to physically visit the property. This is particularly important if the client is not in the same city, state or country as the property that they wish to see. It also reduces the chances of a client booking a viewing with certain expectations in mind and ending up seeing something totally different.
Better agent recruitment
Using AI and machine learning makes it possible for real estate brokers to analyze the market to see where the demand is high, untapped, and expected to grow. This makes it possible for your real estate agency to figure out which area it should hire more real estate agents for and move into. AI systems also reduce the bias that human recruiters may face, thus helping agencies find the best candidates.
Preventing budget overrun issues
A McKinsey study reported that upwards of 80% of big building projects have been completed with budget overruns. AI-powered systems help tackle this issue with some help from robotics and LIDAR Imaging. There are solutions like Doxel which use autonomous robots for analysis through the use of 3D pictures and AI systems to find out about ongoing problems and issues and warn managers about them. Taking a step further, building operations and maintenance platforms like Facilio also offer advanced capabilities like prescriptive and predictive maintenance using Internet of Things (IoT) and AI to define failure scenarios, predict possible faults, and fix assets before they break down.
Such systems have been able to reduce budget overrun by 11% and even track and automatically estimate the profit value of installed products, detecting installation errors quickly and increasing efficiency by 38%.
Mortgage loans make up an enormous chunk of lending in the immovable sector. These tend to be extremely data intensive. Such loans require bank statements, credit history, income verification, and several other documents.
Customers applying for mortgage loans have a headache dealing with all that information, and lenders need to spend a ridiculous amount of time examining and evaluating all the data. Now OCR (optical character recognition) has started being used to read the documents and pull the data. But since most documents are unstructured, only templatized documents could be read by these systems. That’s where AI comes in to back OCR up and make the preliminary decision before passing the documents on to the underwriters.