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Stephen Song, CEO of Diald AI, makes it clear that the massive advantage of using artificial intelligence to evaluate real estate deals is to help uncover key data that otherwise might have gone unseen.SEE ALSO: Deploy or Die: Pressure to Fund Proptech Varies During Uncertain Times “We’ve all had deals that made perfect sense on paper, where everybody agreed it would work — until it didn’t,” Song said during “Winning the Next Deal: How AI Is Reshaping Investment Strategies in CRE,” a virtual event hosted by Commercial Observer Partner Insights...

US commercial real estate investing opportunities favored core property sectors for decades. But recent market forces and new leadership could knock down long-established pillars. Traditionally, commercial real estate owners and investors built portfolios of properties by selecting from a wide array of high-quality assets defined within four core property types: office, industrial, retail and apartment. A diversified portfolio of these core assets provided consistent income from rental growth, sustained value appreciation and minimal variability in performance.1 This approach was generally enough to meet investor objectives and even outperform other financial assets...

Data science is rapidly becoming a cornerstone of success in commercial real estate (CRE) investing. With vast amounts of data available, firms are seeking advanced analytics to gain a competitive edge, optimize portfolios, and enhance decision-making. Despite the industry’s widespread recognition of data’s potential, there remains a great deal of uncertainty regarding its implementation, sophistication, and true impact. SEE ALSO: Sunday Summary: What Is Happening With Government Office Space? This article is a summary of Altus Group’s global research report, The state of data science in commercial real estate investing. This...