I knew we were in trouble when every listing description started sounding exactly like every other listing description.
Every home is “nestled.” Every kitchen is “chef-inspired.” Every backyard is “an entertainer’s dream.” Apparently most American families spend Tuesday evenings hosting elegant dinner parties around the fire pit.
The funny thing is, artificial intelligence didn’t invent this.
Real estate has been recycling the same tired descriptions for decades. We used to write the bad copy ourselves. Now we can generate it in about four seconds. In this article, I will explore how and if AI is making us think less or overthink the real problems we are trying to solve.
Is this progress?
I’ve spent enough years in this business to have lived through plenty of technology that was supposed to change everything: MLS books, fax machines, websites, Zillow, social media, drones, video, virtual tours.
Every few years, another shiny object arrives promising to make the job easier. Friends, there’s no easy button. Technology changes. Real work doesn’t.
I use AI every day, and it has become one of the most valuable tools in my toolbox, but I think we’ve misunderstood what it’s actually good at. AI isn’t replacing good professionals. It’s exposing the difference between people who use the tools to think better and people who expect it to think for them.
Remember GPS?
It’s one of the greatest inventions ever dropped onto a dashboard. It warns us about traffic, finds faster routes and saves time. It has also directed people onto boat ramps and abandoned roads because someone mindlessly followed the screen instead of looking through the windshield.
The problem wasn’t the GPS. The problem was the moment someone stopped thinking. AI feels a lot like that. Here are four tips I recommend thinking about before switching to AI autopilot.
How to use AI in real estate
1. Do the thinking before you open the prompt box
Before I ask AI to write anything about a listing, I want the raw material.
- Why did the sellers buy this house?
- What will they miss?
- Which room gets the best morning light?
- Does the screened porch face the sunset?
- Can the garage actually fit a full-size pickup?
- Does the neighborhood throw a Fourth of July parade every summer?
Those aren’t adjectives. They’re reasons to schedule a showing. Compare that with an agent who climbs into the driver’s seat and types:
“Write an emotionally compelling listing description for a four-bedroom brick home that creates urgency and highlights the home’s unique lifestyle.”
The prompt might be impressive. The actual information about the house amounts to: Four bedrooms. Brick.
AI can only work with what you give it. Before prompting, I try to gather the details that couldn’t have been written about the house next door.
2. Ask AI to organize your expertise, not invent it
One of the best uses I’ve found for AI is taking information I already have and helping me make sense of it.
I’ll give it my notes, observations, market data, competing listings and seller feedback and ask it to identify patterns, organize an argument or show me what I may have overlooked. That’s very different from asking it to tell me what I think.
The same applies to a market analysis. AI can crunch numbers and summarize trends, but it doesn’t know that buyers consistently choose one side of a neighborhood because of the views. It doesn’t know afternoon traffic backs up after school. It doesn’t know the builder changed floor plans halfway through a community because buyers hated the original kitchen.
Experience notices things data doesn’t. Judgment decides which details matter.
3. Make AI show its work
AI sounds remarkably confident even when it is wrong, which means I don’t treat a polished answer as a correct answer.
When I’m using it for research or analysis, I ask questions back.
- Why did you reach that conclusion?
- What information are you missing?
- What assumptions are you making?
- What would change this recommendation?
- What should I verify independently?
Those questions are often more useful than the first answer. The goal isn’t to get AI to agree with me. It’s to use it as another set of eyes on the problem.
4. Never outsource the final read
Every agent has seen the AI-generated listing description that accidentally went live with “[Insert Neighborhood Name]” sitting right in the middle of the copy.
Everyone laughs at AI. I laugh because apparently nobody read it before clicking Publish. AI didn’t publish it. A person did.
I’ve also seen perfectly good listing descriptions replaced with paragraphs about “timeless elegance,” “curated living spaces” and “luxurious everyday living” while nobody bothered to mention the two-year-old roof.
The real AI advantage
I’ve started wondering whether AI is actually making bad professionals worse. Maybe it’s simply allowing mediocre work to be produced faster than ever before.
The flip side is much more interesting. AI isn’t replacing expertise. It’s multiplying it. Maybe that’s the question professionals should be asking right now. Not, “How do I use AI?”
Instead:
Am I using AI to do my thinking?
Or:
Am I using AI to think better?
There has never been an easy button for doing good work. Technology has made it easier to produce work. It hasn’t made it easier to produce good judgment.
Somebody still has to notice the house backs up to a six-lane highway.
Preferably before closing.
The best professionals I know aren’t using AI to think less. They’re using it to think more. They’re asking better questions and feeding AI richer information because they’ve already invested the time to understand the problem.
