How will AI Potentially Transform CRE?
Artificial intelligence and its impact on commercial real estate aren’t necessarily new. Machine learning has helped many companies collect and analyze vast amounts of data in an attempt to identify trends and patterns. This, in turn, has helped determine everything from sales and lease prices, to whether a particular site might be ideal for ground-up construction.
But that’s not all. Generative AI – known by various brand names including ChatGPT, Bard, DALL-E and DeepMind – could help move the commercial real estate sector forward. A recent article by JLL pointed out a couple of things:
1) Respondents to JLL’s 2023 Global Real Estate Technology survey said that “AI and generative AI were ranked among the top three technologies that were expected to have the greatest impact on real estate over the next three years . . .”
2) The same respondents indicated “the least understanding of AI and generative AI,” especially relative to other technologies like blockchain, robotics and virtual reality
The JLL article went on to say that both AI and generative AI would have an impact on CRE in the following ways.
Eye on Labor
Many regard AI as a “good-news, bad-news” scenario. The good news is that the technology will boost productivity. The bad news? People could be out of a job. Yet even with that, the JLL article, in quoting a Goldman Sachs study authored by MIT economist David Autor, pointed out that more than 85% of U.S. employment growth over the past eight decades is due to new job positions resulting from technology.
In the area of commercial real estate, JLL anticipates that AI could have a likely impact on areas like geolocation, asset demand, new assets and product types, revenue and investment and design/space functions.
Eye on Occupiers
It’s probably a given that companies already involved in technology and AI – application development, model hubs and so-on – will need more space for development. But before stereotyping this tenant type, JLL pointed out that the AI focus area with the highest investment was medical and healthcare. This was followed by data management, cloud computing and fintech.
All of this requires new infrastructure as well as increasing space. Generative AI requires “vast computing power and extensive resources,” said the JLL experts. Training also requires computer hardware, high-speed connectivity networks, power supply and data storage. All of this could lead to an increase in certain types of structures, including colocation, hyperscale and edge data centers.
Eye on Proptech
Over the past several years, property technology – proptech – has moved from the sidelines to mainstream usage. “There are now technological solutions for almost every aspect of real estate functions,” noted JLL. These include investment management, design and construction, facilities operations and portfolio management.
This has led to a foundation for AI integration. Real estate AI activities include document sorting and data standardization, construction and capital costs scheduling and leasing/investment “matchmaking” recommendations.
But generative AI applications are still in the early stages when it comes to CRE. Still, some of the early movers in this area are finding that generative AI has been useful in helping with energy management and sustainability and property management.
Article originally appeared in Connect CRE. Author: Amy Wolff Sorter
