The future of real estate and AI

Artificial Intelligence. A buzzword that one hears all too often, but many don’t know its meaning or recognize its value. Others, especially people in the tech sector and especially software, seem to be very enthusiastic about it and usher in a new revolution.

What are AI and Machine Learning (which belongs to the domain of AI)? What do people in the real estate sector think about it and more importantly: What should they think about it? What are the possibilities for the real estate sector?

What are AI and Machine Learning?

Artificial Intelligence is a term that describes computer functionalities that strongly approach or even surpass human cognition. Think, for example, of smart buildings: Buildings that can judge for themselves whether a room or building is too hot or too cold and adjust the temperature accordingly. Machine Learning refers to algorithms (usually mathematical models) that adapt themselves on the basis of data to make predictions, such as for maintenance and rental development.

What does the real estate sector think about AI?

With regards to technology in general, according to Altus Group there has been a shift within the domain of commercial real estate from awareness to adoption. Previously, companies were increasingly aware of technological possibilities, and major change processes have now been set in motion. However, as can be seen in the graph below, AI and Machine Learning are lagging behind. Many companies have automated their processes in recent years, but few have made use of AI and Machine Learning.

Many companies still use spreadsheets for these functions. This may be due to the fact that companies' data is still in silos: Data, usually in spreadsheets, is mostly unintegrated and companies still need to make the transition to well-managed and integrated data. This is why companies still make little use of AI and Machine Learning. Without well-managed and integrated data, these functionalities are difficult to implement.

Because the capabilities of AI and Machine Learning are not used properly, many asset managers, administrators, investors and developers are missing out on important insights. Data-driven real estate investments have proven to yield much higher returns than the current, old-fashioned way (see Skyline AI). Despite the fact that the use of AI and Machine Learning is still scarce, it has increased explosively over the past two years. This strong growth is expected to continue.

What has been made possible so far?

There are many applications of AI in real estate, including revolutionary technologies that deliver huge cost savings. See, for example, Spacemaker, a Norwegian company that uses AI to make recommendations to developers for the best use of development space. Or, for instance, digital real estate agents in the United States such as Redfin, whose technology has already proven far superior to traditional real estate agents. AI is already revolutionizing real estate. The United States is a clear frontrunner in this, but it is inevitable that Europe will follow.

Where are we going?

Now you might wonder: What's the end point? What will have changed with the coming of AI? We imagine a real estate sector in which data-driven trading and brokerage make up the bulk of their markets. Especially the trade in commercial real estate and standard family homes will be fully data-driven. Unique properties might follow later. Even for those properties, advanced valuation algorithms and online brokers could make the traditional broker largely obsolete.

AI algorithms will greatly simplify the real estate development process. Spacemaker already calculates the best type of real estate for a particular plot of land, how buildings are best positioned and in what dimensions they should be built. However, models are going further. AI has also found, for example,  a strong relationship between the number of trees in a neighbourhood and the value of its properties. A strong link has also been found between the name of a project (e.g. The Villas, The Lofts) and its status (and therefore value).

In the future, we imagine AI to also provide insights into which architectural styles and materials are most in fashion. With these insights, developers will be able to make very specific what they want which will save both them and architects a lot of time.

Last but not least, in real estate management and portfolio management, AI algorithms will be able to make predictions about future maintenance costs. Sensitivity analysis will also be done in a data-driven way. Algorithms, combined with huge databases, will be able to recommend changes to real estate portfolios given the investor's goals. They will also be able to recommend investments in sustainability, maintenance plans, marketing, and so on.

Enthusiasm about the future of AI is therefore certainly appropriate. At least, if you know how to use it well as a company.