For years, artificial intelligence has been framed as a threat to commercial real estate, especially offices. But a new forecast from Cushman & Wakefield suggests AI may ultimately create more demand for physical space rather than less.
The report estimates AI-driven productivity gains could increase U.S. demand for industrial, office, and retail real estate by roughly 12% over the next decade, adding an estimated 330 million square feet of occupied space.
AI’s Ripple Effect Beyond Data Centers
While much of the AI real estate conversation has centered on the explosion in data center construction, the report argues the technology’s impact will spread much further across the built environment.
Industrial properties are expected to see some of the largest gains, particularly warehouses, logistics facilities, and manufacturing space tied to increasingly automated supply chains and inventory systems.
The report notes that these projections do not include data centers themselves, but rather the surrounding ecosystem of facilities needed to support AI-driven economic growth.
Office Demand May Change, Not Disappear
The forecast also pushes back against the idea that AI will permanently weaken office demand.
Instead, AI adoption could accelerate an existing divide in the office market, with companies concentrating around newer, more adaptable, high-quality buildings while older offices continue to struggle.
New office construction in the U.S. has slowed dramatically compared to historic levels, potentially tightening supply for premium workplaces even if overall job growth moderates.
That trend could change how employers think about the future workplace: fewer offices overall, but greater competition for spaces designed around flexibility, collaboration, and technology integration.
Uncertainty Still Looms
The report emphasizes that AI’s long-term economic impact remains difficult to predict.
Researchers modeled several possible outcomes, ranging from rapid AI expansion to scenarios where automation replaces more workers than expected. The firm’s baseline projection — considered the most likely — assumes gradual adoption across industries between 2025 and 2035.
