Imagine being able to input architectural specifications and design parameters into an artificial intelligence (AI) chatbot, and have it generate a code-compliant, permit-ready floor plan within a matter of seconds.

Not long ago, that would have been considered science fiction, but today these ideas are in development thanks to AI-focused companies such as Hypar, one of several platform developers seeking to revolutionize the architectural and real estate industries.

And architects like Stephen Coorlas, founder and principal architect of Coorlas Architecture in Northbrook, Illinois, have already begun testing their potential.

Above and below: Renderings of an education campus from a generative AI program. (Coorlas Architecture)

“Programs such as Hypar can accelerate the modeling process, saving hours or even days, by automating tasks traditionally performed by humans,” said Coorlas. “The time saved can be used by architects to more responsibly source materials and systems, while giving more thought to how properties are developed in terms of programming, planning, and the usefulness of a site.”

Although Coorlas is passionately exploring the potential of these new AI-assisted design tools, his efforts are not the norm within the architectural discipline, at least for now.

In April, ULI Young Leaders attended a webinar that addressed the current and future impact of AI on the real estate industry and the obstacles and challenges to its adoption.

Nikki Greenberg, founder of Real Estate of the Future.

Titled “What Buildings Will Be Like When AI Takes Over,” the one-hour event was hosted by Nikki Greenberg, a former architect and founder of Real Estate of the Future.

“The power of AI is increasingly being leveraged across the full-building life cycle and it’s a true game-changer for the industry,” said Greenberg. “Generative AI is already being used to design floor plans and conduct feasibility studies by architects and development teams.

“Building management and operations teams benefit from machine learning systems that optimize mechanical systems to lower carbon emissions and help asset portfolios meet their carbon reduction goals,” said Greenberg.

“This is only the start of it,” she said. “The options of what the technology can do will be plentiful, and the systems will grow exponentially smarter.”

Many of the day-to-day tasks performed by real estate professionals have already been impacted by AI, including the way in which property prices are set, said Johns Hopkins Carey Business School assistant professor Luis Quintero.

“With the help of machine learning algorithms, real estate professionals can analyze vast amounts of data to identify trends and patterns and provide suggested listing prices with varying expected sales times in the market,” said Quintero. “Sellers can then set prices based on how quickly they need to sell.”

Virtual tours have also become more interactive and personalized due to the technology’s ability to create 3D models, with AI-powered chatbots often taking on the repetitive tasks of scheduling appointments and answering common questions, he said.

“AI is even being used to help reduce fraud, analyzing and synthesizing data that can help detect a buyer trying to use a false identity or a seller misrepresenting a property,” said Quintero, a researcher for Johns Hopkins University’s 21st Century Cities Initiative.

But that’s only a small portion of its potential. The problem is there are a number of barriers that must be overcome before AI can be widely adopted, with many in the traditionally conservative real estate industry unaware of its capabilities and others fearing it could cost them their jobs.

There’s also a substantial upfront financial investment involved in purchasing the technology, setting up the systems, and changing the way teams do their work, said Greenberg, not to mention concerns surrounding incorrect results, bias, and privacy issues.

“One of the greatest problems is data,” said Greenberg. “If your data is wrong or in a form that the AI cannot understand, then the conclusions will be inaccurate.”

When selecting a platform, businesses need to set realistic expectations for the functions it can carry out given the organization’s infrastructure.

“Sales teams from technology companies may overpromise and that can lead to disappointment when a company’s systems are not designed to work in tandem with the technology it adopts,” said Greenberg.

Company leaders must also be able to delineate the clear advantages to making the substantial financial investment that’s needed, i.e., cost savings down the road and improved efficiency in the delivery of projects.

“AI is not going away, so companies that embrace the technology will be leaders in the industry and those who do not will be laggards,” said Greenberg.

As new AI-powered platforms continue to be introduced, universities are beginning to incorporate courses into management and finance curriculums and even some real estate programs to prepare the next generation and assist those currently working in the industry.

The NYU School of Professional Studies Schack Institute of Real Estate recently began offering a class in data analytics. Developed by clinical assistant professor Timothy Savage, the course includes discussions of the history of commercial real estate analytics tools as well as their potential to change the industry in the future.

“Traditionally the industry has used AI to perform simple tasks like rent and vacancy forecasting,” said Savage. “But as we move forward from AI 1.0 to AI 2.0, we are beginning to see it used to design the urban built environment. … The potential tools of AI 3.0 will ideally have the ability to improve our decision-making abilities in the commercial real estate industry, not by replacing human beings but by complementing our skill sets.”

“Those who will be left behind will be those who refuse to adapt,” said Savage. “AI reminds us that we must all be continuous learners in life.”

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