For executives, access to powerful tools that help them make informed decisions is essential to remain competitive against mounting competition and fast-changing trends. “The potential for AI [artificial intelligence] to transform business, industries and society has been mounting for decades,” noted a 2024 report from JLL, a real estate think tank. “The technology’s proficiency in writing, drawing, coding and composing has compelled corporate leaders to consider both the opportunities and threats AI presents for their future.”
Introducing AI to real estate should not be problematic. “Any business that involves data is a good target for AI,” said a November paper from the Motley Fool, a financial and investment advice company. “There’s plenty of data in real estate.”
According to the JLL report, developers can significantly benefit from both analytic AI and generative AI (Gen AI). The latter uses data published online to respond to queries, while the former analyzes locally stored data to make projections.
To benefit from either technology, real estate developers have to change their mindsets. “One industry in which AI’s transformative power has been missing … is real estate, a historically slow adapter of new technologies,” business consultancy McKinsey said in a November paper.
New vs. old
According to JLL’s research note, “AI and Gen AI are ranked among the top three technologies … expected to have the greatest impact on real estate over the next three years.”
McKinsey said analytic AI is the “more familiar version” for developers. It is “goal-oriented and focused on activities such as predicting values for a future forecast or assigning categories to segment customers.” It includes “AI-assisted forecasting, [which has] altered how investment professionals think about the future, and dynamic pricing models have changed how [real estate] charges for goods and services.”
Gen AI “focuses [on] generating new content, designs or solutions,” according to McKinsey. Open AI commercialized the technology in 2022 when it launched ChatGPT for free. Since then, Microsoft has embedded it in its corporate solutions (Copilot), while other developers have created their own versions of the technology.
For developers already relying on analytic AI, generative AI is another tool to expand the existing system’s capabilities. “Gen AI has not replaced analytic AI; instead, its open-ended and creative nature introduces a new frontier of use cases that analytic AI does not address,” McKinsey stressed.
Developers with low analytic AI capability should focus on leapfrogging to Gen AI, said the paper. For them, the technology will be “a fresh chance for the real estate industry to learn from its past and transform itself into an industry at technology’s cutting edge.
Improving the business
According to Max Liul, a data science specialist at Integrio Systems, an AI tools developer, Gen AI’s benefits start with selecting the project’s location. “AI-powered software is capable of providing … information about [various] areas’ crime records, natural disaster probability, transportation and parking facilities, local school’s stats and reviews, entertainment, recreation and dining options,” he said in an undated blog post. “It can also tell … the amount of sunlight reaching a particular property.”
Gen AI can also help with pricing those properties by “utilizing current property data … and hundreds of factors that could potentially affect the property … to evaluate [its] future value,” Liul said. That would save the agent and potential buyer “the chaos of predicting a property’s market value.”
From a marketing perspective, Gen AI helps developers improve their online and real-world presence with “new creative content, including text and images.” It would also help decision-makers generate “insights from unstructured data, interpreting conversations [on social media] and querying large data sources.”
Gen AI also helps real estate agents identify genuine potential buyers from window shoppers via behavior analysis or chatbots. “It’s quite usual for people to visit real estate sites as a recreational activity,” Liul said. “It’s smart not to consider such customers as your potential leads.”
Developers could then use Gen AI to recommend the best locations from their portfolio to buyers, McKinsey said. Also in this stage, Gen AI can “craft negotiation transcripts” based on “information about a tenant, the property and the market,” said McKinsey.
Tenants will benefit from Gen AI-powered “tools such as conversational chatbots,” McKinsey noted. Potential uses include managing tenant requests, such as routine maintenance. The chatbot also could “identify more complex questions and flag them for a [human] specialist, and “observe conversations and written responses and suggest ways to improve communication.”
Gen AI improves property management by automating heating, ventilation and air conditioning operations, thus reducing energy costs, Luil noted.
Developers could use AI for research and administrative work. “A gen AI-powered tool can summarize key themes across leases, such as how much rent is expected monthly or what … local environmental, social and governance compliance laws could affect leases,” McKinsey said. It “can scan across leases for a particular parameter (for example, all leases with a rent price … below a certain level).”
McKinsey estimates that real estate companies gain at least 10% in net operating income through more efficient operating models, stronger customer experience, tenant retention, new revenue streams and smarter asset selection.
Difficult implementation?
Despite the hype, developers find it challenging to implement and scale use cases for Gen AI. That is “not surprising,” McKinsey said. “Deriving competitive advantage from gen AI is not … simple … Many things have to go right in an organization to make the most of the opportunity.”
One prerequisite is having departments check the “toxicity” and “hallucinations” of Gen AI results. The former creates “problematic content … that would violate … laws.” The latter provides “false answers without sharing that the tool’s [results are] uncertain.” Identifying and rectifying training data biases is essential for avoiding those problems.
Developers should modify their hierarchies to reflect where Gen AI tools fit in an organization. “Operating models and jobs may need to be redrawn to match the new focus of work,” noted McKinsey. “New roles and capabilities may be needed.”
Another challenge is the high financial and capacity investment in cybersecurity to protect the vast data Gen AI needs. Meanwhile, engineers must be aware of relevant laws the AI tool could violate, mainly regarding data privacy.
To benefit from Gen AI, developers need to “do more than just learn how to use off-the-shelf products,” said McKinsey. That requires “aligning the C-suite around a business-led road map tied to a specific part of the real estate value chain.”
In the coming years, real estate developers will need to be careful when implementing Gen AI solutions as “regulations are hitting a new milestone in 2024,” noted JLL’s report. “Following the U.S. Executive Order on AI at the end of October 2023 … the EU AI Act has recently been approved by the European market. Regulators and lawmakers in a number of other countries, including China, Canada and Australia, are actively advancing their own AI efforts.”
That means adopting AI will become increasingly complicated. Nevertheless, the JLL report stressed that “strategic management of these complexities holds the promise of unlocking unprecedented productivity advancements for the real estate sector.”
This article first appeared in July’s print edition of Business Monthly.
