Use Cases of AI in Real Estate
Take a deeper look at the potential applications of artificial intelligence in real estate and how brokers and agents can use AI to improve their businesses.
Artificial intelligence (AI) is now a reality outside science fiction films. In the world we live in today, AI is used frequently. Some of what artificial intelligence has to offer may already be familiar to architects and real estate developers. So will anyone who has ever interacted with a chatbot. You might not have realized that the pleasant customer service representative you are live-chatting with is not actually a person.
The key is this. There will always be artificial intelligence. That holds true for the real estate, construction, and technology industries. Hence, future and current professionals must prepare for a sector where AI automation is the standard.
Artificial intelligence is making inroads in the real estate industry, with realtors incorporating algorithms and data pipelines into their decision-making processes. To what end? Read on!
AI in Real Estate
Although "artificial intelligence" sounds cool, what does it mean? AI is a branch of computer science that uses intelligent algorithms to process vast amounts of data, allowing the software to recognize logical patterns that can be applied to various tasks. Artificial intelligence doesn't always mimic the human mind. AI performs significantly better than human thought.
AI in the real estate industry serves a variety of purposes. A typical example is finding a client a suitable house to buy or a mortgage. Smart algorithms quickly find the ideal home for a customer by scanning through various data inputs like property price, location, local crime rate, debt history, etc.
Obviously, the above example is not the only way artificial intelligence is used in real estate. That's why we would like to share some additional cases with you.
Use Cases of AI in Real Estate
There are multiple examples of how real estate companies use artificial intelligence to increase their competitiveness and efficiency. Let's examine the most popular use cases of AI in real estate.
Using multiple listing services (MLS) to navigate a housing market has become a no-brainer in the Internet age. Homebuyers can choose a property by specifying their preferences for location, square footage, price, and building design. Even these specifications do not provide customers with immediate answers, so they must spend considerable time searching for a home that meets all expectations.
Zillow devised a method for making home searches quick and easy. The company collects and processes all customer preferences using AI algorithms to show only those houses that meet a client's requirements. Customers can quickly find the right property because the intelligent recommendation system displays only the most relevant sale offers.
While finding the perfect apartment is the primary source of frustration for homebuyers, reaching out to relevant groups of customers is the responsibility of real estate agents.
⦁ First and foremost, an agent must identify clients ready to purchase a home. Many visitors to MLS websites are just looking around and have no plans to buy a home anytime soon.
⦁ Second, because a realtor may specialize in a specific property type, identifying customer groups based on location, willingness to pay, or property preferences can be difficult.
Compass employs artificial intelligence for real estate agents, which assists realtors in qualifying leads based on custom criteria. Compass includes an AI-powered CRM (Customer Relationship Management) that notifies real estate agents when potential clients are active on the MLS platform or any other property search website. Realtors can track customer behaviors in this manner and plan their actions accordingly.
Investment and Marketing
It's natural for property investors to strive for the highest possible return on investment (ROI). Real estate investment entails analyzing financial statements to make informed decisions.
Property investors must be aware of the effectiveness of risks, benefits, and financial leverage to make sound decisions. Furthermore, the real estate market remains volatile due to the coronavirus pandemic, so property investors should exercise extreme caution when making financial decisions.
GeoPhy's Evra solution provides real estate valuation using an artificial intelligence approach. The software predicts a property's price change and capitalization rate using multiple data sources.
Furthermore, the solution analyses and compares various factors influencing the asset's value by displaying market data trends on a dashboard. Regardless of what the future of the real estate market holds for their business, AI-driven predictive analytics significantly assist real estate investors in making more informed decisions and responding to market trends.
Many companies are looking for ways to improve their performance. One example of how businesses can do this is through smart workspace utilization. According to JLL research, 40% of office/commercial property space is underutilized, implying that a company appears to be wasting a lot of money when renting a larger office.
IBM's Tririga artificial intelligence solution is used to use office/workspace better. The software collects data from smart sensors and Wi-Fi hotspots to learn how employees interact with their workspace. All analytics are presented in a simple and straightforward format, allowing office managers to reduce office waste significantly.
Construction Project Planning
While purchasing property is difficult, building one is even more difficult. Construction firms are constantly exposed to various risks associated with property development projects.
Overruns in resources, budget constraints, or even unforeseeable environmental factors frequently disrupt construction projects and hold contractors accountable for foreseeable outcomes. For these reasons, construction firms desire the ability to anticipate potential project issues.
It should come as no surprise that artificial intelligence can provide a solution to these issues. Doxel is an AI-powered solution that tracks the asset's constructed elements and estimates the earned value of each component using autonomous sensors.
The software can display the entire construction site in 3D, provide project progress data, and show how the construction will look after reaching a specific milestone. The solution promises to reduce operating costs by nearly 11% while increasing construction team productivity by 38%.
Needless to say, real estate companies want to make their customers' lives as easy as possible, especially regarding paperwork and transactions. Customers are concerned about whether they can buy/sell a house at a reasonable price, whether their mortgage interest rate is reasonable, and whether any legal issues will interfere with the purchasing process. With so many options available to homebuyers (such as choosing between government-sponsored FHA loans and conventional loans, when to lock a rate, and so on), technical issues should be the last thing on their minds.
When a real estate company mortgages a house, the client must be able to repay the debt. An evaluation of the customer's financial situation is also required.
Click.AI is an automated underwriting service that allows real estate firms to sign ten times as many deals as their competitors. To reduce time spent on repetitive tasks, AI algorithms automate documentation filing, financial calculations, and customer cash flow evaluation. Furthermore, automating these tasks ensures that neither the property company nor the customers face any errors or risks during the transaction.
Benefits of AI in Real Estate
The use of AI in real estate has proven to be beneficial. With the automation of business processes and improved market analysis, the following benefits of AI in Real Estate have become clear:
Humans have always been prone to making mistakes. Smart algorithms, on the other hand, do not make mistakes. They cannot tire themselves out or ignore details like humans. So, with the proper AI model training, you can get almost any Real Estate information you want.
Research is required to produce a construction project or show potential clients some homes. You must conduct solid research to present it to your stakeholders. Furthermore, not all information can be easily and quickly disclosed. However, this is not the case with artificial intelligence in real estate. Smart algorithms can assist you in figuring out where to build homes, what your main users want, and how to offer better recommendation services. The analytics will only benefit agents in this case. In addition:
⦁ A lot of manual work is automated by AI.
⦁ AI improves security and fire safety systems.
⦁ AI predicts the value of the real estate.
⦁ AI makes buildings 100% more appealing to buyers.
Artificial intelligence detects errors in any Real Estate documentation. Agents work with these documents daily. That is why it is critical to employ AI in this situation. The outcomes are more precise, and more key consumers may be involved. Furthermore, the Real Estate industry deals with a large amount of data daily. So, to the greatest extent possible, AI can make the process safer and better.
Unlike humans, AI can work at any time of day or night without needing to rest. That is its primary advantage. You cannot compel the Real Estate agent to assist you outside of working hours. However, you can use artificial intelligence. Give algorithms a task, and they will complete it and learn from the results. That is how you can save money and time while pleasing your potential customers.
Start-ups Using AI in Real Estate
We've compiled a list of 4 companies using AI and bots to transform the real estate sector.
Location: Boulder, CO
How it's using AI? For homebuyers, HouseCanary offers unparalleled clarity through cutting-edge products and technology. To assist customers in making knowledgeable decisions about properties of interest, the company provides a sizable collection of tools, information, and updates. People can navigate the residential real estate market and choose the ideal home if they can access up-to-date property information and personalized searches.
How it's using AI? At Redfin, artificial intelligence essentially complements human agents by taking on some labor-intensive facets of their job. With the aid of an AI matchmaking tool, Redfin has automated making property recommendations. Data suggests that users click on the matchmaker's suggestions more frequently than homes that match their search criteria, indicating that it is more in tune with their preferences than they are.
Location: New York City
How it's using AI? CoreData, a SaaS platform powered by AI from Cherre, intelligently compiles and indexes real estate data from tens of thousands of sources, including internal data silos. CoreData, based on the high-frequency trading platforms used in the financial sector, incorporates and learns from data in real-time, transferring insights from all user data to each individual’s user data.
Location: San Francisco
How it's using AI? AI is used by Divvy Homes to tailor each applicant's application for a rent-to-own mortgage. The application form adapts dynamically to the client's described financial situation, adding additional questions for clarification and removing unnecessary ones. Underwriting calculations, which take minutes at Divvy but can take a week with traditional lenders, are also sped up by artificial intelligence.
Challenges of AI in Real Estate
Artificial intelligence in real estate presents significant challenges, but they are not unachievable.
⦁ First, AI works well in any industry when it can learn on its own. An AI specialist is required to develop solutions with automated learning capability to enable automated AI functions. Fortunately, this problem can be solved by a skilled team of specialists!
⦁ Second, AI tools must be used in accordance with the law, with data security as a top priority. Data protection from potential hackers is one of the most challenging issues facing artificial intelligence and real estate. It is a big responsibility to handle the personal information of thousands of real estate clients. However, many AI experts are developing novel approaches to data security against cybercrime.
⦁ Finally, data scarcity is a significant challenge when employing AI in the real estate industry. The quality of AI algorithms is heavily dependent on the data they receive and use to generate sufficient output. Having both high-quality and large amounts of data allow your AI software to make better decisions. The main issue arises when the available data sets are insufficiently diverse. For example, information about private and commercial properties, building profiles, sales history, rents, tenants, and lease agreements. However, advanced data mining practices can help the real estate industry overcome the challenge of data scarcity.
Let's sum things up! AI is transforming the world's businesses, and the real estate industry is no exception. Property owners, investors, dealers, and clients benefit from AI algorithms' smart decision-making abilities. Nothing is impossible in the entirely digitized real estate industry, from automated transactions to virtual property viewings.
Using AI in the real estate industry reduces property management costs to half of their original value and gives you a competitive advantage. However, cyber-security risks are a constant threat that will only be addressed through smart innovation. The key is to adhere to AI-related legal regulations and to keep a close eye on data security initiatives.
Are you ready to boost your Return on Investment (ROI) with advanced artificial intelligence (AI) algorithms?