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Summary:

Two Realberry development leaders share how AI may change what gets built, not only how quickly work gets done. They discuss underwriting, hospitality discovery, offices, autonomous vehicles, and experiential real estate, and offer questions to ask when a sponsor says it uses AI.

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Artificial intelligence (AI) is already changing how companies operate. For real estate, the bigger question is whether it may also change what gets built, where, and for whom.

That question drove a recent webinar sponsored by Realberry and hosted by MarketsGroup. Will Little, Chief Development Officer, and Jason Cruce, Executive Vice President of Hospitality Development, each have more than two decades of experience in the field.

Efficiency Is Only the Start

Will pointed out that AI's operational benefits get plenty of attention, and Realberry expects to see them too. Anyone who builds financial models in Excel, he said, may find AI makes the work easier and helps remove errors. But that is true for almost any business.

What fascinates Will is the product. How may AI change what developers deliver to consumers, and what the built environment looks like as a result? In his view, that is the more interesting question for real estate. Doing the same things faster is an upgrade. Changing what gets built is a different kind of shift.

AI in the Underwriting Room

According to Will, Realberry's teams have seen major time savings: work that used to take days can now be done in hours. In practical terms, that is a much shorter wait between an idea and a first look at the numbers.

Jason, whom Will described as a champion of AI integration across the firm, sees a second benefit. He encourages his team to treat large language models (LLMs), the AI tools that respond to written prompts, as a conversation partner and not only a calculator. Asking a basic question such as “Is there something I’m missing here?” can lead the model to offer context, suggest an alternative approach, or point to something worth adding to a building.

When Discovery Starts With a Prompt

How do travelers find a place to stay? Jason believes the answer is changing. He sees more consumers turning to AI assistants, describing what they like, and asking for hotels or destinations that match. In his view, the era of browsing traditional booking sites is likely behind us.

For hospitality developers, that may change how an asset is introduced to the world. Jason described structuring marketing so a property can surface for specific queries and prompts, building the physical experience into the digital environment as well.

Rethinking the Office, Not Retiring It

Does AI mean less office space? Will thinks a different outcome is more likely: different office space. In his experience, office occupancy has picked up in large markets such as New York and San Francisco since the pandemic, which suggests people still want to gather and collaborate. At the same time, AI may allow organizations to scale with far fewer people.

Imagine a tenant that once leased 200,000 square feet producing the same work within 6,000 to 8,000 square feet. That is a footprint roughly 96 to 97 percent smaller. He was clear that office still has a place in Realberry's portfolio, but the task is to be specific about who the end users are and which markets suit them.

Location may still be a defining word in real estate, but what a location is for is shifting. Will observed that people now work in more kinds of places than ever, including spaces not designed for work. Jason saw it firsthand at a hotel Realberry owns in Santa Monica, where he estimated about half the people lounging on the pool deck had laptops open. Realberry is responding by upgrading network capacity in its hotels and adding communal spaces.

Jason also sees opportunity beyond the office. As AI reduces commuting time and adds efficiency at work, people may have more room for experiences. He pointed to growing demand for mixed-use environments with food and beverage, wellness, event space, and boutique hotels.

Autonomous Vehicles and the Parking Question

What happens to parking if cars become a service? Will called it one of the more interesting questions in real estate. The amount of land devoted to personal vehicles in cities and suburbs is, in his word, “staggering.” From his Denver office window, he can see at least three parking structures that autonomous vehicles could one day make obsolete.

In his view, he encourages developers to consider a world in which no one owns a car. If that world arrives, the opportunity may lie in converting land used to store vehicles into new uses that add density and create places people love.

Jason extended the idea to the air. Autonomous vertical takeoff vehicles, he said, could make parts of the planet reachable that roads don't serve, opening the door to resorts and destinations that could not exist before.

Will added an anecdote he described as just that: Realberry is receiving growing requests for rooftop and parking-area space that could be used to launch and land such vehicles.

Why Experience May Matter More

If AI makes some activities more efficient and some space less necessary, does it raise the value of what technology can't easily replicate? Will believes it does. “As a developer, I have to believe that’s true,” he said. He observes people spending discretionary income on experiential real estate: places to bring family or a partner, enjoy quality time, and maybe get a little work done.

Jason sees the same split in hospitality. In commoditized hospitality, where guests are often driven by loyalty programs, he sees much less interest in new development. Growth, in his view, is concentrated in experiential and luxury hospitality, where guests want a sense of place, a real connection, and service. That is why Realberry leans into place-driven design, authentic local connections, and a thoughtful food and beverage program, with AI helping the team understand what consumers want through targeted market research. “It’s more than just building a building,” Jason said.

How does a developer know it is working? Will listens for a reaction. On project tours, the more people say “Oh, wow,” the more conviction he has that the team is on the right track.

The same logic may reach beyond hotels. Will noted that indoor malls, for decades a main way people shopped, have largely faded with a few exceptions, while outdoor lifestyle centers have become far more common. The brands and products are the same, he said, but consumers wanted to be outside. Jason added that retail is becoming more experiential too, with lounges and run clubs.

Will personally expects the gap between experiential real estate and everything else to widen. He also stressed that developers still need to think about product for every segment of the US population.

Longer Lives, New Stages

An audience member asked how longer life spans may factor into what gets built. Will noted that, over the long sweep of history, technological advances have tended to improve and extend lives. He sees healthcare as an area of promise. If people live longer, he said, real estate may need to serve those moving into a new stage of life.

Questions to Ask About a Sponsor’s AI

Another audience member put it plainly: many sponsors say they use AI, so how can investors tell who is actually adapting? Jason and Will offered a few questions worth asking.

First, how is the sponsor using it? Jason distinguished creative use from pure analytics, and asked whether the technology benefits only the sponsor or helps produce a better project for the whole investor group. Feeding a model and requesting outputs is easy, he said. Interpreting the output, spotting a trend, and adapting to it is harder.

Second, where is it making mistakes? Will said anyone who uses AI daily sees its shortcomings. It has real benefits, but it is not perfect yet. Asking a sponsor where they struggle with the technology may reveal how deeply it is built into their work.

Third, who is checking the output? Jason noted that colleagues early in their careers may lack the context to recognize when a result looks inaccurate. AI tools can produce hallucinations, answers that sound plausible but are wrong, and a user who does not check sources and citations may accept them. Jason called that a danger that has to be mitigated.

Building What’s Next

AI may make the work faster, but the larger shifts may come from what people want and how they move, work, and gather. Tools may change. The aim, as both speakers put it, remains creating places people love.

This is the beginning of what’s next. It is an area where curiosity, experience, and healthy skepticism may serve developers and investors alike.