The commercial real estate industry could realize $110B to $180B more in value with the proper application of generative artificial intelligence, McKinsey Global Institute estimates. The company calls generative AI “open-ended and creative,” a technology that introduces uses that previous versions of AI didn't have.

Most of that potential remains just that, however, since many real estate entities, which operate in an industry that has long been slow to adopt new tech, find it hard to implement AI, with the nature of the new technology posing challenges.

“This is not surprise: deriving competitive advantage from gen AI is not as simple as just deploying one of the major foundational models, and many things have to go right in an organization to make the most of the opportunity,” McKinsey said in its report.

Still, the opportunity in AI is there, and McKinsey detailed some of the ways that CRE can take advantage of it.

Generative AI can sift through the mountains of dense documents generated by commercial deals, summarizing key themes across leases, including rental trends or market forces impacting the leases, McKinsey said.

Generative AI can also assist as a “powerful copilot” in managing tenant requests and lease negotiations, enable the visualization and creation of new revenue streams, and help make faster, more precise investment decisions, the report says.

In construction and development, generative AI can develop architectural plans to optimize physical space, such as the patterns of customer movement through retail or the utilization of conference rooms in an office setting, according to McKinsey.

Achieving such outcomes with generative AI won't be simple but will be worth the effort, the report says.

“Winners are willing to experiment, iterate, and self-disrupt,” the report says, requiring an investment in a squad of engineers and designers familiar with generative Al and ready to focus on value-adding uses.

“Getting value from gen AI requires that executives be willing to question the industry’s traditional hierarchies and operating models and, most important, to accept a new technology layer throughout the organization,” McKinsey said.