JLL has finalized a deal to acquire the artificial intelligence firm Skyline AI, a specialist in applying the technology to commercial real estate opportunities. The real estate services giant said the deal will close soon but didn’t specify a price.
Chicago-based JLL plans to use Skyline AI’s artificial intelligence and machine learning systems to forecast multifamily property values, identify cost savings, seek out investment opportunities and make other business decisions, such as the timing of rent increases.
Skyline’s tech processes data from more than 300 sources, according to JLL, tracking attributes such as owner information, property characteristics, demographics, and transaction and debt history for roughly 400,000 U.S. multifamily properties.
Over time, the goal of the Skyline AI platform is to ferret out patterns and determine which information is the most useful for investment and leasing decisions, JLL said.
“It’ll give our real estate clients deeper and faster insights,” JLL Technologies co-CEO Yishai Lerner told The Wall Street Journal.
JLL manages more than 5.4B SF worldwide for its clients. Skyline AI was founded in 2017 by serial tech entrepreneurs Guy Zipori, Amir Leitersdorf, Iri Amirav and Or Hiltch. JLL Spark, a JLL venture fund, has been an investor in Skyline AI since 2018.
JLL is hardly alone in harnessing AI toward commercial real estate ends. Oxford Properties Group, which has a 150M SF real estate portfolio, is undertaking Project Alpha, an AI-powered technology that uses information from around 50 data sets to create models of properties in markets worldwide.
Archipelago, a company that uses AI to better understand commercial property risk, raised $34M in Series B funding earlier this year to expand its platform, which currently serves over 330,000 commercial properties with a total insured value of $2.3 trillion.
AI, which runs driverless cars, virtual assistants and warehouse robots, is now also being used to allow construction machinery, such as excavators and bulldozers, to run autonomously.
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