Introduction

Generative AI (gen AI) is maturing at an auspicious moment for the real estate industry. Investors have mountains of both proprietary and third-party data about properties, communities, tenants, and the market itself. This information can be used to customize existing gen AI tools so that they can perform real estate–specific tasks, such as identifying opportunities for investors at lightning speed, revolutionizing building and interior design, creating marketing materials, and facilitating customer journeys while opening up new revenue streams.

Although gen AI has only recently captured the public’s imagination, AI has been fundamentally changing the way the world does business for decades. This more familiar version of AI—also known as analytical AI—is goal oriented and focused on activities such as predicting values for a future forecast or assigning categories to segment customers. It is already embedded in parts of the business world: AI-assisted forecasts, for example, have altered how investment professionals think about the future, and dynamic pricing models have changed how several industries charge for goods and services. One industry in which AI’s transformative power has been missing, however, is real estate, a historically slow adopter of new technologies.

Gen AI represents a fresh chance for the real estate industry to learn from its past and transform itself into an industry at technology’s cutting edge. Gen AI has not replaced analytical AI; instead, its open-ended and creative nature introduces a new frontier of use cases that analytical AI does not address.

For all the hype that gen AI has received to date, many real estate organizations are finding it difficult to implement and scale use cases, and thus have not yet seen the promised value creation. This is not surprising: 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.