Artificial intelligence or AI is used — often unnoticed by humans — in more and more areas. This is also the case in the real estate industry, where the capabilities of neural networks open up new opportunities for the sale, operation, and maintenance of buildings. The areas of application in the real estate industry are diverse. Four areas stand out in particular.
Neural networks can be roughly differentiated by the extent to which they take on tasks autonomously. In some areas, AI acts without human intervention; in others, it merely supports him in various activities. Systems of different types can also be found in the real estate industry. The solutions presented below are already in use or ready for the market within the next few years.
But why AI? Homo sapiens is good at making connections between “obvious” facts. For most of us, the following argument should seem logical: “People with children buy a property with a garden more often.” Artificial intelligence is powerful because it does not perceive the world in three dimensions without social imprint. Thanks to machine learning, it sees and processes information fundamentally differently than living beings.
As a result, neural networks are increasingly able to establish connections between aspects that are less obvious to humans: “People with children aged 2–4 are most likely to buy a property with a garden on Tuesdays when it is not raining. When the outside temperature is more than 18 degrees. “
AI is more than Siri and Alexa
Everyday life shows part of the answer: programs recognize faces and unlock the smartphone, Siri and Alexa organize our daily life and cars drive (partially) autonomously. AI is a helpful, self-learning technique for assessing risks, organizing vast amounts of data, finding solutions, and making processes more efficient.
Organizing data or finding solutions is a significant advantage for the real estate industry, which generally produces vast amounts of data. But that requires intensive preparatory work.
Before a machine or a program is even able to learn by itself, these artificial helpers must first be “trained.” Before an application can automatically read and evaluate rental agreements, the system must first be programmed. The quality of the output, therefore, depends entirely on the input of the human operator.
Artificial intelligence accelerates document review
The advantages can, therefore, be seen quickly. Europe seems to be more progressive in throwing cherished traditions overboard, provided that it serves to improve efficiency.
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Currently, AI is mostly used in transactions for information management, such as for large real estate portfolios. In connection with a data room, all relevant information on the individual property or entire portfolios comes together and can, for example, be analyzed before a transaction.
Artificial intelligence as a real estate agent
Such analyzes require the collection of a lot of data — called Big Data. Suppose a sufficient amount of anonymized behavioral data is available. In that case, neural networks can predict with a very high degree of probability when, where, and at what price users of a web platform will rent or buy real estate.
Whether it’s a restored old building in the city center or a modern passive house in the country — these systems also know which type of property potential buyers are most likely to strike and can provide them with relevant offers.
An AI as a real estate agent? An experiment on the Denver real estate market shows that this works. For this purpose, a test candidate with an imaginary budget selected three objects from the urban area that he liked the most. Based on this information, three human real estate agents from Denver and an artificial intelligence sent him two further suggestions for buying property in Colorado’s capital.
As it turned out, the objects selected by the AI were most liked by the test candidate. The potential advantage for companies is that such systems can be used to address customers more precisely and provide them with relevant content.
AI in building automation
The built-in building technology in objects has been increasing steadily for years. That makes perfect sense. With IoT-enabled devices, sensors, and other technologies, real estate can be operated more efficiently and with less energy.
Also, the convenience of the user increases. However, this goes hand in hand with increasing complexity. To achieve maximum efficiency, it is, therefore, not enough to collect and evaluate the data. Because buildings are subject to various dynamic forces, such as the weather or a changing occupancy of rooms.
One possibility is to put the collected data in a temporal context. In this way, patterns of operation and use can be identified over hours, days, or months. In combination with building technology, artificial intelligence can recognize such trends. This enables operators to better predict certain developments, such as expected energy consumption.
The above approach to building automation can also be used in the area of property management. When is there a high probability of a need for renovation in which buildings? In which properties are high personnel costs to be expected in the coming quarter? Depending on the data collected, artificial intelligence solutions will make it easier to answer these questions about property management in the future.
Another possible application in this area is on the user’s side. An example: The tenant of an apartment detects damage in the property. With the help of a virtual assistant, she transmits information about the deficiency to facility management. An AI automatically processes the transmitted data to be used immediately by an employee for further processing.
Automation in building security
Neural networks are also increasingly being used for surveillance, as they — unlike a single security guard — can process an unlimited amount of video signals. Image processing systems recognize when a camera in the building is recording a movement and, in a matter of seconds, discuss whether it is a matter of people, animals, or an object.
If it is a person, facial recognition is used to determine whether they are in the monitored area without authorization. If this is the case, the porter will be informed. Still other systems recognize, for example, at airports, whether a person is carrying dangerous or prohibited objects. Shoplifters watch out: Artificial intelligence should now also be able to register suspicious behavior,
Before an artificial intelligence can independently recognize documents such as a building permit or a lease, goals must be defined first. The software is “trained” with the data on these goals. The advantages of artificial intelligence in the real estate sector are only fully exploited if the quality of the algorithms developed is right, so the input ultimately determines the quality of the output.