In South Florida’s competitive real estate market, artificial intelligence tools are changing how homebuyers research properties — but according to Ximena Ulloa, a realtor with The Giulietta Ulloa Group at Berkshire Hathaway HomeServices EWM Realty, relying on them too heavily can be costly. Speaking from her experience in Miami’s Key Biscayne market, Ulloa identifies critical gaps in what AI can deliver — from misrepresented listing data and street-level blind spots to the absence of vetted professional networks — making the case that local human expertise remains irreplaceable where it matters most.
AI Misreads Listing Data
One of the most common ways AI tools mislead buyers is through misrepresented listing data — a problem that no algorithm can catch because it requires physical inspection and local knowledge to identify.
Ulloa describes a recurring situation in Miami’s Roads neighborhood, where properties are sometimes listed as four-bedroom, three-bathroom homes when the actual configuration is a three-bedroom, one-bathroom main house with a separate one-bedroom, one-bathroom structure in the back. “There are a lot of homes where it’s two homes — a main home and then in the back there’s a construction that sometimes has one bedroom and one bathroom — and they get listed as four bedrooms, three baths, when it’s not true,” she explains.
The aggregate bedroom and bathroom count matches the listing, but the lived reality does not. An AI system trained on that data will treat these properties as equivalent to a true four-bedroom home — and a buyer making decisions without a local agent may not discover the discrepancy until already emotionally and financially committed.
AI Misses Street-Level Details
Beyond listing accuracy, AI tools have a fundamental blind spot regarding street-level knowledge — the kind that determines whether a property actually fits a buyer’s daily life. “ChatGPT doesn’t often look at location,” Ulloa notes. “They don’t understand if it’s a pass-through street. They don’t understand if there is some kind of school or work building around it that’s going to affect a lot in terms of traffic.”
In Key Biscayne specifically, certain streets are more susceptible to flooding than others — a detail with significant financial implications as Miami’s drainage infrastructure faces increasingly intense weather. However, Ulloa acknowledges the city is actively working on drainage improvements to mitigate the problem.
The same applies to subtler quality-of-life factors: which buildings have tight-knit communities, which neighborhoods are gaining or losing residents, and which blocks feel quiet versus noisy at night. These are details that experienced local agents accumulate over years of transactions and that no AI tool currently captures reliably.
AI Lacks Vetted Connections
Buying a home requires more than finding the right property — it requires a team of competent professionals, from inspectors and mortgage brokers to closing attorneys who know local contract norms. Ulloa points out that while AI can generate a list of names, it cannot identify who has a track record of thorough work or who a local agent has stopped recommending because of past problems. “A lot of people don’t have good contacts for inspectors that’ll do a good job, and that will advise you correctly,” she says.
She also emphasizes the importance of shopping around for mortgage rates rather than defaulting to an existing bank relationship. “A lot of times you have a relationship with a bank — it doesn’t mean that the bank is giving you the best rate, because they’re not comparing it, they’re not shopping around, they’re giving you their prices.”
Knowledge of who performs and who doesn’t lives in professional relationships built over years, not in databases.
Agents Educate, Not Dismiss
Rather than dismissing AI outright, Ulloa’s approach is to help clients understand what these tools can and cannot do before decisions are made on incomplete information. Education has always been a cornerstone of her practice — from ensuring buyers have a proper pre-approval before falling in love with a property outside their budget. This extends to walking clients through the post-Surfside regulatory environment and the specific characteristics of individual buildings and streets that determine whether a property is worth the investment.
“I think that a lot of people are starting to think that maybe I don’t need a realtor — maybe I can just do it myself, put everything in ChatGPT, and they’ll guide me,” she says. “I don’t think that’s correct at all. I think that real estate is very nuanced.”
Ulloa frames real estate as more than a financial transaction — it is an emotional milestone that shapes the next several years of a buyer’s life. “Real estate is such an emotional purchase and a milestone in your life that you don’t want to complicate it more and have regrets,” she says. “It’s a very big purchase, and both financially and mentally, it helps guide the next few years of your life.” For Ulloa, local expertise is not a preference — it is a necessity that no algorithm can replicate.