We Searched ChatGPT for Realtors in San Antonio, Columbus, Detroit, and Indianapolis. Here’s What We Found.

San Antonio is the fastest-growing large city in the United States, and it has a relocation engine unlike almost any other market in the country. The military footprint here is massive — Fort Sam Houston, Randolph Air Force Base, Lackland Air Force Base, and several other installations generate a constant, high-volume stream of Permanent Change of Station relocations into Bexar County and the surrounding metro. Military families operating under PCS orders typically have 30-to-60-day windows to find housing in a city they may have never visited. They have no existing agent relationships in the destination market. They research everything online first, systematically and fast.

Layered on top of the military relocation demand is a growing corporate economy. Toyota’s North American headquarters is here. Valero Energy is headquartered here. USAA, one of the largest financial services companies in the country, is headquartered here. These employers have been drawing corporate relocations from all over the country — and the professionals moving to San Antonio for those roles are arriving from coastal markets where AI tool adoption is high. A tech professional transferring from San Francisco to a corporate role at a major SA employer is not picking up the phone to cold-call agents. They are opening ChatGPT.

When we ran the search for San Antonio realtors, the result was strikingly thin given the size of the market. Bexar County has thousands of licensed agents. A handful of names returned — agents who had been covered in local San Antonio media, regional Texas business publications, or national real estate rankings. The agents who specialize in military relocation — a meaningful and active specialty in this market, one that requires genuine expertise in VA loans, military base proximity, and PCS timeline logistics — were almost entirely absent. The military families who most need that expertise are precisely the buyers who are most likely to use AI to search for it.

San Antonio’s growth trajectory makes this gap wider over time, not smaller. The market is adding buyers faster than most cities in the country. A growing share of those buyers are arriving with AI-researched agent shortlists already in hand. The agents who aren’t in those results aren’t getting considered — regardless of how long they’ve been working the market or how many transactions they’ve closed.

Columbus is Ohio’s fastest-growing city, and Intel’s announcement of a $20 billion chip manufacturing complex in New Albany put the metro on the national radar in a way it hadn’t been before. That announcement triggered a wave of corporate relocation interest from people who had never previously considered Columbus — engineers, project managers, and supply chain professionals from Seattle, San Francisco, and New York who are now researching the market from across the country. Those buyers are tech-industry native. They use AI for everything. They are not calling real estate agents cold. They are asking ChatGPT who to call.

Columbus also has one of the largest student and young professional populations in the Midwest, anchored by Ohio State University. Younger buyers — particularly those in the 25-to-38 age range — are among the highest AI tool adopters in any demographic. This is a population that researches restaurants on ChatGPT before booking a reservation and uses AI to summarize lease agreements before signing. They are absolutely using AI to research real estate agents. And Columbus is affordable relative to coastal markets in a way that makes buyers willing to commit earlier and from farther away — which means they’re making decisions before they visit, based entirely on online research.

What we found when we searched ChatGPT for Columbus realtors reflected the market’s fragmentation. Columbus doesn’t have one dominant real estate brand. No single team or brokerage has built the kind of regional media presence that drives consistent AI citation. The agents who showed up had been mentioned in Columbus Business First or regional Ohio real estate publications — not because they were the most productive agents, but because they had press coverage that AI had indexed. Most of the market — including agents doing significant volume in Westerville, Dublin, Upper Arlington, and German Village — returned nothing. The fragmented market actually makes AI visibility a bigger differentiator here than in places with dominant players: if no one owns the AI recommendation, the first agent who builds the citation infrastructure owns it.

Detroit’s real estate market is in a genuine rebound. Downtown development driven by Bedrock and Quicken Loans has brought significant investment and media attention to the urban core. The automotive industry’s pivot to EVs — Ford’s EV division, GM spinoff operations, Stellantis investments, and the supplier ecosystem surrounding all three — is pulling in tech and engineering talent from outside the traditional Detroit labor pool. Amazon has a meaningful presence in the metro. Young professionals are driving demand in Royal Oak, Ferndale, Grosse Pointe, and Birmingham at a pace that has pushed inventory to near-historic lows in desirable neighborhoods.

The buyers arriving in Detroit for these tech and corporate roles are coming from places like Seattle, the Bay Area, and Chicago. They are AI-native. When a software engineer relocating for a Ford EV role starts looking for a house in Birmingham or Royal Oak, they are starting that research the same way they research everything: asking an AI model. Detroit’s traditional real estate community is deeply embedded and genuinely skilled — agents here build long-term relationships and have loyal client bases. But that local loyalty does not produce the indexed, third-party citation presence that AI requires. Most Detroit agents have almost zero digital footprint outside of Zillow and local platforms.

When we searched ChatGPT for Detroit realtors, the results were the thinnest we’ve seen in any major market we’ve tested. Detroit barely registers in national AI real estate content. The names that came back were agents connected to national luxury networks with PR infrastructure, or agents who had received coverage in Crain’s Detroit Business. The specialists working Birmingham, Royal Oak, and Ferndale — the neighborhoods with the most urgency-driven buyer demand — were essentially invisible. Low inventory plus urgency means buyers are making fast decisions. A buyer who gets to Detroit and has already decided on an agent from AI research is not starting over. The agents who aren’t in those results are starting at a structural disadvantage that only compounds as this buyer cohort grows.

Indianapolis has quietly become one of the top relocation destinations in the Midwest. It shows up on top-10 inbound migration lists year after year without the national profile of a Columbus or a Nashville — which means the buyers arriving here are doing their research with less publicly available information to work from. Major employers including Eli Lilly, Salesforce, and Cummins are drawing corporate relocations from tech hubs and pharma corridors on both coasts. A life sciences professional relocating from Boston or San Diego for an Eli Lilly role is arriving from one of the most AI-native buyer demographics in the country. A Salesforce engineer relocating from San Francisco is not cold-calling agents. They are asking AI.

The buyers researching Indianapolis from Chicago, New York, and San Francisco before making the move are doing so from positions of geographic unfamiliarity. They don’t know the difference between Carmel, Zionsville, and Fishers. They don’t know whether Broad Ripple or Meridian-Kessler is the right fit for their lifestyle. They are asking AI to orient them — and they’re asking AI who to call for help. The agents who show up in those early research sessions are the ones who get the call. The ones who don’t show up don’t get considered, no matter how well they know the submarkets.

When we searched ChatGPT for Indianapolis realtors, the result was nearly empty. Very few Indianapolis agents have any AI footprint at all. The names that appeared had connections to national real estate networks with media presence, or had been mentioned in Indianapolis Business Journal features. The gap between visibility and market activity was as wide as any market we’ve tested. Indianapolis is a growing market pulling in buyers with high AI tool adoption, and the local agent community has almost no presence in the channel those buyers are using. That’s an opportunity gap, not just a threat — the first agents to build indexed citation presence here have an essentially uncontested position.

San Antonio, Columbus, Detroit, and Indianapolis are four different markets with different price points, different buyer profiles, and different competitive structures. But the agents who appeared in ChatGPT results across all four had built the same underlying infrastructure. After running this experiment across more than a dozen metros, the pattern is consistent enough to describe with confidence.

• 1.Indexed third-party citations in credible publications — In San Antonio, that meant coverage in local media and regional Texas business publications. In Columbus, mentions in Columbus Business First and Ohio real estate media. In Detroit, Crain’s Detroit Business and national luxury network PR. In Indianapolis, Indianapolis Business Journal features and national relocation rankings. The agents who showed up had their names cited by name in sources AI has indexed and treats as authoritative. Production volume, Zillow ratings, and social media following are not legible to the model. Published citations in third-party sources are.
• 2.Consistent, complete profiles across authoritative aggregators — Full bios on Zillow, Realtor.com, and Google Business that described their specialty, geographic focus, and experience in specific, parseable language. AI builds confidence in a name by seeing it consistently described across multiple independent sources. The visible agents had profiles that triangulated across platforms with clear, keyword-rich descriptions. The invisible agents — even high-volume producers — often had thin or generic profiles that gave AI nothing to anchor to.
• 3.Not: social media presence, website design, or review count — We checked across all four markets. Agents with large followings, polished websites, and hundreds of five-star reviews were no more likely to appear in AI results than agents with minimal online presence. AI search is a different game from SEO and social media — it rewards published, indexed, third-party documentation of local expertise. Most agents have never focused on building that trail because it didn’t matter until recently. It matters now.

In all four markets, the AI visibility landscape is still wide open. The agents who are showing up got there largely by accident — press coverage they didn’t optimize for, rankings that mentioned them incidentally. The field hasn’t been claimed. If you’re in San Antonio, Columbus, Detroit, Indianapolis — or anywhere else — and you want to know where you actually stand right now, run this 2-minute test to check whether ChatGPT can find you.