The post-pandemic climate has yielded a precarious commercial real estate market. So, wouldn’t it be nice to be able to ask your chatbot to scour the market and find a property that’s a good investment? Well, one can ask that question, but you won’t get a viable answer—at least not yet. AI isn’t capable of performing the multi-faceted analysis that goes into assessing the practicality of a potential transaction, but it can execute a host of tasks that provide vital assistance in investors’ decision-making process.
The performance of due diligence is key to making a successful real estate investment—in any market. It’s all about having the right information, and tons of it, to make an informed decision. And while AI-based platforms can’t find a “good” investment, they can be an invaluable tool for property research. These platforms combine the use of algorithms and a wide array of historical data to complete numerous tasks ranging from property valuations to trend forecasting in a fraction of the time that a team of mere humans would require to amass the same information.
So why is utilizing an AI-based platform purpose-built for commercial real estate better than relying on responses from some of the other AI solutions like ChatGPT? It boils down to data that the AI is being trained on. All of the tech companies are training their AI on different data sets, and none of them are focusing on property data. For AI to be useful when it comes to real estate decisions, it needs to know a lot of specific information about the relationship between properties, trends, and investment returns. These can come from general sources like MLS data or from third-party vendors like CoStar, RCA, Yardi, VTS, CompStak, and the like.
But to really train AI to have a competitive advantage, real estate companies need to use their own data. “The vast majority of things that we’re hearing around AI solutions is somewhere between hype and utter nonsense,” claimed L.D. Salmanson, co-founder of Cherre, a real estate data management and insights platform. “The only way anything that ever gets built on top of these tools that is of any meaning whatsoever is it’s sitting on a repository of data that’s clean and useful.” As good as that sounds, getting the data to a point that is useable at scale can be a massive undertaking, one that can prove to be too much of a barrier to entry for some firms.
Clean and useful data, or accurate and deeply diverse data—and lots of it—is the foundation of using artificial intelligence in general in real estate investment. Standard is a company that uses an AI protocol to transform corporate systems for accelerated growth in a variety of industries, and for the real estate industry, the company’s platform enables investors, brokers, and agents to complete transactions with greater efficiency. “Our model matches buyers, sellers, and assets by tapping into countless data points across property listings, economic trends, demographics, and more. We leave no stone unturned to uncover hidden market opportunities,” said Aaron Rafferty, CEO of Standard. Looking ahead, the company will deliver even more granular insights for clients on an individualized basis by expanding its data ingestion and fine-tuning its AI algorithms. “We are expecting to be able to provide projections on the hyper-local level and identify emerging developments and investment hotspots earlier than ever before,” Rafferty added.
AI can provide real estate guidance on a variety of levels, generating useful information based on thousands of data points, including current and past market information, property history, company acquisition and disposition patterns, the lending climate, and assumptions or predictions regarding rent growth and interest rates. These are all factors that real estate investors take into account when considering potential transactions, and AI can cull that information and provide predictive analysis to inform their acquisition activities.
There are limits to the sort of questions AI can answer. “If you’re trying to answer things like where should I buy something and you ask the question around the office sector, that’s a really complex question that’s not going to be solved in its entirety by AI,” Salmanson said. “Can AI assist in this process? Truly. Can AI solve this problem? Absolutely not.” With proper data as a resource, AI can, for example, provide information on the best-performing markets and how those markets might perform in the future or which buildings encompass features that are most desirable among tenants. But AI platforms can’t respond to a query and identify a specific asset and say, that’s the one; that’s the best building to add to your particular portfolio for these reasons.
AI can’t be a property-buying guru and pinpoint a good deal because there are copious variables to be considered. AI might be able to identify the correlations, but only a human can apply those correlations to the real world, at least for now. Even some of the biggest players in the commercial real estate world, like Brookfield or Starwood, have centralized their internal portfolio data and possess the financial resources to acquire practically every relevant data set available but can’t elicit an informed and accurate response to the query about the guaranteed bargain-basement deal.
Data sets can be contradictory. What might be listed as “tenant improvements” in one data set might be “TI” or “tenimpro/lease.” You get the idea. And then there are the deal factors that don’t easily fit into numerical form. “The ability of AI to be able to say something like pick this property, even though the bid-ask spread is smaller than others and more likely to close. You can’t know that,” Salmanson noted. “You have to think about who the seller is, and what their motivation is, and what kind of psychology they have going on right now. That’s just not a reasonable expectation. The data to be available to answer those questions is not a real thing.”
We haven’t even started to crack the surface of what AI can do in real estate; there is so much more AI will be able to do to aid commercial real estate investors in decision-making in the not-too-distant future. For now, AI still serves as a valuable instrument for decision-making in acquisitions and dispositions. In short order, it could be a tool that spots potential investments before anyone else can. But it remains to be seen if it will ever fully replace the human intuition that is so critical to every real estate deal. AI might not replace the senior acquisitions manager, but it might be coming for his research staff.
