FRESH TAKES ON BIG IDEAS

Real estate has been slower than other industries to adopt analytics for decision making and day-to-day operations. Historically, less data has existed and been accessed in real estate compared with other industries. After all, it has traditionally been a business about buildings and their physical use, with less of a focus on the adoption of digital tools.

But generative AI (gen AI) has the potential to change the real estate industry paradigm for several reasons. First, actors in the industry are better prepared to adopt this wave of technological advancement than they were with previous advancements. Today, there is vastly more technology embedded in every aspect of a building, from building management systems to elevators to apps that interface with staff and building users. Modern skyscrapers have the potential to generate millions of data points every day that can be aggregated, processed, and analyzed for superior decision making. Furthermore, real estate organizations have built infrastructure to help capture and harness the potential of this data by making investments in data and technology over the past five to seven years. 

Second, the industry used to face a big barrier when it came to experimenting and using AI models. To even get to a proof of concept, companies had to invest heavily in data, infrastructure, and talent. But gen AI has democratized access, as tech firms and venture capital–backed start-ups have made big investments in large language models that can be tailored and adapted to various contexts. That has greatly reduced the cost and time it takes to deploy gen AI models, enabling brokerage firms, title companies, lenders, and real estate investors and operators to experiment at an unprecedented pace.

This technology is coming to fruition at a crucial time for the real estate industry as companies think about what the market truly demands and focus on assets’ operating performance. Using the latest analysis from the McKinsey Global Institute, we believe that gen AI could generate $110 billion to $180 billion or more in value for the real estate industry. Most aspects of the real estate value chain should have applications for gen AI, starting with how buildings are designed and constructed. That doesn’t mean that gen AI will come up with something a human couldn’t have. But it can run many iterations, customizations, and combinations that may be cost or time prohibitive for an architectural or engineering firm to perform. Gen AI has the potential to make it easier to personalize buildings, tailor spaces to end user needs, and incorporate learning from existing spaces into new ones.

Marketing content for new listings can be largely automated using gen AI, and the content can be hyper-personalized for each audience. A home could be virtually staged with modern, minimalist design, for instance, and a listing description could be customized to match the preferences of a specific member of the target buyer audience. Gen AI could also automate communications between building users and staff. The technology, for example, could be used to help tackle maintenance requests or rent payment questions in an entirely automated way, freeing up building staff to focus on more complex tasks that require human intervention.

“We believe that gen AI could generate $110 billion to $180 billion or more in value for the real estate industry.”

To get started, real estate companies will need to accelerate their data and analytics transformations. Step one is creating advantage with proprietary data through aggregation and normalization of relevant data sets from both the organization’s own systems and third-party service providers. This data should be a means to an end, enabling specific decisions and use cases that can deliver tangible business value.

The next step is thinking differently about talent and capabilities. Just as real estate companies compete for the best design, construction, investing, and asset and property management talent, so they will want to think about data scientists and technologists as critical to their competitive edge.

Step three is reconfiguring analog business processes to data- and analytics-informed processes. Changes in business workflow will be required to understand when to take inputs from a gen AI model versus when there should be human oversight. The key is to start experimenting early and to build the internal skills and capacity needed to benefit from gen AI.

Are the rewards worth the effort? I think that question is going to become irrelevant in the next five to ten years, as many processes and workflows across the industry are likely to be either greatly enhanced or automated by gen AI. The more relevant question is, “How can real estate organizations not just upgrade but completely reimagine what they do?” What would you do differently, for example, if a significant amount of middle-office and back-office activities of your real estate company could be automated? How would you reallocate that investment into creating superior customer experiences and more dynamic, responsive, and environmentally conscious buildings? There is no question that the technology will improve exponentially over the coming years. Competitive advantage will be captured by those who have learned how to harness gen AI’s power in every aspect of what they do—that includes embracing a future where long-sacred operating models and processes can be reimagined.

ABOUT THIS AUTHOR

Vaibhav Gujral is a senior partner in McKinsey’s New York office.