The use of Artificial Intelligence (AI) is expected to lead to a transformation of the commercial property landscape. The extent and timing of the economic effects, as well as their specific impact on commercial properties, are the subject of the current study “AI Impact on Commercial Real Estate: The Next 10 Years” by Cushman & Wakefield. This study outlines four scenarios with varying probabilities of occurrence, which translate general prognostic statements to real estate usage types and regions such as EMEA, the Americas, and Asia-Pacific.
The base scenario, which has a 50 percent probability of occurrence, assumes a gradual introduction of AI. The resulting productivity gains would successively support stronger economic growth. Mr Kevin Thorpe, Chief Economist and Head of Global Research at Cushman & Wakefield, states that demand for office space will not be eliminated by AI but rather restructured. In the short term, companies might focus on efficiency, which would lead to a slowdown in hiring dynamics while new technologies are integrated. In the long term, however, higher productivity, increasing corporate profits, and new business formations would enable a revitalisation of office demand.
Mr Thorpe adds that the question of where growth occurs is crucial. AI reinforces existing bifurcation trends by increasing demand for high-quality, flexible spaces in leading talent markets while simultaneously putting pressure on existing properties. A growth and productivity scenario, with a 15 percent probability of occurrence, assumes accelerated AI penetration, efficiency gains, and the reinvestment of productivity gains. This would strengthen demand for high-quality office space, reduce vacancies, and promote a focus on top quality. For retail, logistics, and residential properties, this scenario would already reinforce positive dynamics, for example through higher household income growth or increased throughput in logistics.
An adverse scenario, reflecting
The fourth scenario, whose probability is estimated by the authors at five percent, considers an increased displacement of human labour by AI. In this case, productivity would indeed rise, but employment and demand would remain weak, leading to structurally higher office vacancies. Market performance would be strongly polarised by quality and adaptability. For retail and residential properties, a lack of income growth would result in increasing vacancies. In the logistics sector, vacancies would remain elevated as automation dampens labour-driven space demand. While structural supply constraints could support prices and demand in these sectors, the growth impetus of the more positive scenarios would be absent.
In conclusion, Mr Thorpe summarises that the analyses indicate an expansive rather than shrinking effect of AI on the economy. The crucial question for the property market is not the disappearance of demand, but its redistribution across markets, usage types, and quality segments. Location, quality, flexibility, and access to talent would thus become even more important performance factors.
