Despite predictions to the contrary, there hasn’t been a large-scale crash in commercial real estate. While foreclosures continue to rise, many owners have managed to navigate the high-interest rate environment. But, the combination of high interest rates, limited financing sources, and low supply has brought sales volume down significantly. This has intensified competition among brokers for each deal. Unlike in past buyer’s markets, sellers are not offering deep discounts, pushing price points to the edge of financial viability. As a result, brokers are retooling their organizations to be more streamlined and efficient, with many turning to advanced technology to help them achieve this.
Any real estate deal involves a considerable amount of data. Unlike equities or commodities, real estate data comes from a variety of sources, many of which are in inconvenient formats like PDFs. Consequently, each deal involves substantial data entry, a task often delegated down the chain, sometimes to individuals with little training and oversight. This is an ideal job for AI. Property companies have been turning to AI to manage the unstructured nature of their data. As early as 2016, JLL partnered with the German company Leverton to automate their lease management. In a previous Propmodo interview, JLL’s CTO explained that this ongoing process remains incredibly complex for a company of JLL’s size, which produces millions of documents annually in dozens of languages.
Other major brokerages have followed suit. CBRE has built an “AI playground” for the company to experiment with use cases. “We’ve created a self-service AI playground, adding about 150 users weekly through word of mouth,” said Sandeep Davé, Chief Digital Officer at CBRE. “It’s a place where our teams can query real estate data, have models point to real estate documents, query those documents, and translate them into multiple languages.”
Every large brokerage has invested in AI to streamline the underwriting process. Their approaches vary widely, with some partnering with startups and others leveraging established tech giants. Cushman and Wakefield opted for the latter, announcing earlier this year that they would use Microsoft’s Azure AI to integrate artificial intelligence into their workflows. Conversely, Marcus and Millichap have entered a strategic partnership with the San Francisco-based tech firm Archer, hoping to give their brokers an edge.
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Newmark is one large brokerage that seems to have made fewer investments in AI. The “AI perspectives” page on their website remains blank. This doesn’t appear to reflect a lack of belief in AI’s growth potential, as they launched a dedicated data center and cloud computing real estate division last year. Instead of significant tech investments, they have focused on aggressive talent recruitment and are the only global brokerage to increase headcount amid the commercial real estate slowdown.
Newmark likely hopes their AI needs can be met by the growing number of tech companies building products for real estate. There are more companies than ever offering document parsing services. Major PropTech players like MRI and Yardi have AI offerings, as do popular brokerage-focused tech firms like Buildout. Additionally, many companies provide document abstraction for CRE, such as DocSumo. Some specialize in adding AI to specific real estate platforms, like Proper.ai.
Commercial brokers are looking for every possible way to save time, reduce costs, and expedite deal closures. As they turn to AI for assistance, they have more options than ever before. Most large brokerages are either partnering with AI providers or developing their own capabilities. Others are utilizing the growing number of available tools, albeit for a price. If the market continues to stall, we will likely see even more investment in AI to give struggling brokers a competitive edge. We will also see who emerges victorious in the AI arms race.
Brokerages that have invested heavily in the technology expect to see returns through increased deal volume and easier recruitment. Those who have waited hope to find it easier to hire specialized tech companies to build complex software rather than develop it in-house. Ultimately, as more brokers become equipped with AI, those who can best harness its capabilities will reap the most benefits, regardless of the amount of money invested in its development.
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