Nearly 330 million square feet of commercial real estate demand will be generated across the US over the next decades from artificial intelligence (AI), according to a new study by Cushman & Wakefield (NYSE: CWK).
The study projects a total net absorption over the next 10 years that surges from a pre-AI forecast of 2.7 billion square feet to just over 3.0 billion square feet through 2035 – a 12.2% spike.
Furthermore, the study predicts AI’s near-term impact on hiring as companies prioritize efficiency over headcount expansion. The study is forecasting an average of 400,000 to 700,000 jobs annually through 2030, with office-using employment lagging in the near term as businesses recalibrate. Over time, however, an accelerated growth in employment will be fueled by new business formation and the emergence of new industries.
“It’s important not to lose sight of the supply side when assessing the outlook for office,” said James Bohnaker, principal economist and co-author of the report. “The US economy has historically delivered around 50 msf of new office product annually, but over the next few years, deliveries are tracking closer to just 5 msf. At the same time, AI will accelerate the bifurcation trend, with demand shifting toward high-quality, adaptable space. We are underbuilding the product the market needs most, which should put downward pressure on high-quality vacancy, even in a slower job growth environment.”
The report predicted the industrial real estate sector will be the strongest beneficiary of the new AI era, with an additional 298.5 million square feet of absorption. Multifamily real estate will benefit indirectly through stronger job and income growth, with Class A product in talent-dense markets positioned to outperform.
“AI widens the range of outcomes for real estate more than it shifts the central path,” said Kevin Thorpe, chief economist at Cushman & Wakefield. “Performance is increasingly going to be determined at the micro level, by the quality of the asset, the flexibility of the space, the depth of the local talent pool, and how well operators and investors adapt to a market where dispersion is the defining feature.”
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