Out of curiosity, I asked ChatGPT, Gemini, and Perplexity to recommend local real estate brokerages in Charlotte, NC. I wanted to see how AI viewed them and if the same names appeared consistently.
The result? Across 12 responses, I received 48 different real estate brands and agents.
Thirty-six appeared just once across the three tools. Only four names showed up in all three.
For real estate agents hoping AI search will recommend them, the inconsistency raises a question: What makes a brand visible in ChatGPT or Gemini?
I dug into the outputs to see what lessons real estate marketers could learn, if any, from this mini-experiment.
How I Prompted AI for Real Estate Agents
I used ChatGPT, Perplexity, and Gemini in late October 2026. I asked each one the same four questions a Charlotte buyer or seller might ask:
- Who are the best real estate agents in Charlotte, NC?
- Which real estate brokerage should I use to buy a home in Charlotte?
- Who is the best luxury real estate agent in Charlotte?
- Who should I hire to sell my home in South Charlotte?
Three AI tools and four questions equals twelve answers.
Counting AI Mentions
I counted each real estate agent or brokerage once per AI tool when comparing the overlap, even if the name appeared in more than one answer from that tool. Separately, I also counted how many of the 12 responses mentioned each name.
I also used an Incognito window and logged out of my paid accounts to limit any influence from prior search history on the results.
What AI Search Revealed About Local Real Estate Agents
Different real estate agents and firms popped up nearly every time.
The lack of overlap was most noticeable in two questions: which brokerage to use, and who to hire to sell in South Charlotte. Asking the same question in a different tool produced a different shortlist every time.
Being recommended for one client question doesn’t guarantee you’ll be recommended in another prompt. It shows why you need general and specific search questions.
| Name | ChatGPT | Perplexity | Gemini |
| John Bolos Group | ✓ | ✓ | ✓ |
| Stone Realty Group | ✓ | ✓ | ✓ |
| The Redbud Group | ✓ | ✓ | ✓ |
| Andy Bovender Team | ✓ | ✓ | |
| High Performance Real Estate | ✓ | ✓ | |
| Dickens Mitchener | ✓ | ||
| Fagan Realty Group | ✓ | ||
| Jill Moyer (Redfin) | ✓ | ||
| Josh Finigan | ✓ | ||
| Julia Savage (Redfin) | ✓ | ||
| Kyle Bender (eXp) | ✓ | ||
| Nancy Braun (Showcase) | ✓ | ||
| Pridemore Properties | ✓ | ||
| Stephen Cooley RE Group | ✓ | ||
| The Premier Team (RE/MAX) | ✓ |
The tools also seemed to rely on different sources. For its South Carolina picks, ChatGPT highlighted agents with substantial Google Business Profile review numbers. Perplexity appeared to prioritize RealTrends rankings, and it labeled firms’ own “#1” claims as unverified. Gemini pulled and cited broker websites.
Which Charlotte brokerage appeared most often in AI search?
One firm did show up often: Dickens Mitchener. It appeared in 6 of the 12 answers, more than any other name. It was the only real estate brand all three tools gave in response to the luxury question.
So I looked at what the firm has published. One of its undated blog posts is titled “30 Dickens Mitchener Agents Rank Top in Charlotte”. It’s short, around 350 to 400 words. It names the agents, says where they placed in RealTrends’ annual rankings, and ends with a line to contact the firm. The meta description sums up the claim in one sentence.
The post achieves several content best practices. In answering the basic W’s- who was recognized, what they achieved, where they are ranked- it presents specific, organized information that is easy for AI to parse and analyze.
It isn’t perfect. There’s no author or publication date. The post doesn’t link to the RealTrends list, which updates every year. However, you can verify the claim by visiting RealTrends’ 2026 Best Real Estate Agents in Charlotte ranking, which does list multiple Dickens Mitchener agents. The 2026 names and the blog post names differ, suggesting an earlier date for the agency’s announcement.
Still, I can’t establish with certainty that this post influenced AI to serve the agency. What it does do is hint at a practical way for real estate professionals to publish verifiable information highlighting their expertise.
Which real estate agents appeared in all three AI search tools?
On the general “best agents” question, three names showed up in all three tools: Stone Realty Group, The Redbud Group, and The John Bolos Group.
What made them verifiable by each AI? Currently, any trends or similarities about why AI chose them are harder to pin down. I did note a few characteristics:
According to RealTrends, those three names each report between $189 million and $359 million in sales. Two names that only one tool mentioned report $34 million and $43 million.
Two of the three have 5-star reviews on their Google Business Profile with over 600 reviews. A third had a 4.9-star average with 149 reviews, but a 5-star rating on Zillow with almost 800 reviews.
The common thread is that all three have demonstrated top-performing sales histories and strong third-party reviews.
Could those credibility signals contribute to their visibility in AI search? Possibly. Industry rankings and customer reviews give AI tools independently published information to reference when recommending agents.
But this small sample doesn’t show whether sales volume, review counts, or another factor explains their repeated appearances.
The weakness in evaluating AI Search results
This is a snapshot, not a ranking. I ran each question once, on one day. Some may have pulled my general location and used my address as a factor when deciding who to show me. A rerun will change the lists.
Twelve answers are a small sample, and prompting isn’t perfect.
What Charlotte’s AI recommendations tell real estate, marketers
Don’t judge how AI sees your real estate business from one answer. Ask a few tools, a few different ways, and see what comes back.
- Test the questions your clients actually ask.
Don’t check only ChatGPT to see if your brokerage’s name appears. Try buyer, seller, neighborhood, and specialty searches in multiple tools. Record if you or your competitors appear and what the tools say about each business.
- Look for evidence behind the recommendations.
Does the response cite an industry ranking, customer reviews, a business profile, or the company website? Those details point you toward information worth checking or improving. They don’t prove how AI ranked its choices.
- Make your expertise easy to verify.
Publish current, specific information about your agents, markets served, sales experience, and independently documented accomplishments. Check that your name, brokerage, and details match everywhere.
I put together a free guide that walks you through the check in about 10 minutes: Can ChatGPT Find Your Business? It has a scorecard to log what each tool says and a short list of what to fix first.
Try it, and tell me what you find.
This article used AI to assist with research, outlining, and revision.
Leave a Reply