We Searched ChatGPT for Realtors in New York City and Los Angeles. Here’s What We Found.

New York City has more than 50,000 licensed real estate agents — one of the most densely competitive markets on earth. The sheer number of licensed professionals relative to available inventory makes it unlike any other metro we’ve tested. It is also a market with an exceptionally large share of buyers who arrive having already done extensive research: finance workers relocating from Chicago, Boston, and international financial centers; buyers from Europe, Asia, and South America researching US real estate from overseas; and transplant professionals moving from major tech and corporate hubs who treat AI tools as the starting point for any significant purchase decision.

International buyers in particular are worth understanding. A buyer in London or Singapore researching Manhattan apartments is not going to ask a friend for an agent referral. They are going to start with an AI query. They may never speak to an agent who isn’t in those results. For that buyer, the ChatGPT answer is the shortlist — and if your name isn’t on it, you don’t exist.

When we ran the ChatGPT search for New York City realtors, the results were heavily skewed toward luxury names and national brands. A handful of agents associated with high-profile Manhattan transactions, agents who had appeared in national press coverage of the luxury market, and one or two names affiliated with internationally recognized brokerage brands consistently came back. The agents actually moving volume in Brooklyn, Queens, the Bronx, and Staten Island — the boroughs where the majority of New York City real estate transactions actually occur — were almost entirely absent. The specialists working Astoria, Sunnyside, Park Slope, Flatbush, and Riverdale didn’t show up at all.

This creates a specific dynamic worth understanding. In a market with 50,000+ agents, only a handful have any AI visibility — and nearly all of them are concentrated in the Manhattan luxury tier. The outer boroughs, where most buyers and most agents actually operate, are essentially an uncontested field. The agent who builds a strong AI citation presence in Astoria, or in Park Slope, or in the Bronx doesn’t have to outcompete thousands of people. They have to outcompete nearly nobody, because no one in those markets has built any AI footprint yet.

For a full breakdown of what’s driving AI visibility in the New York City market, including what the visible agents have that everyone else doesn’t, see our NYC-specific analysis.

Los Angeles is the second-largest metro in the United States and has tens of thousands of licensed real estate agents. It draws one of the most diverse buyer pools in the country: tech workers migrating south from San Francisco and the Bay Area, entertainment industry professionals relocating from New York and Atlanta, international investors from Asia, Mexico, and the Middle East, and an enormous base of California internal migration from the Bay Area, the Central Valley, and other high-cost coastal metros.

What makes LA particularly relevant to this experiment is how many of its buyers make decisions remotely. A software engineer moving from San Francisco to Los Angeles may be committed to the move for months before they ever visit to look at homes. A buyer relocating from New York for an entertainment role typically has a short window to find housing — they’re researching agents from across the country, choosing someone before they land. International buyers are doing the same thing from further away. In all of these scenarios, the buyer is forming a shortlist through digital research — and AI is increasingly where that research starts. By the time they make contact with an agent, the decision is often already made. If you aren’t in ChatGPT’s results, you don’t get a call.

When we searched ChatGPT for Los Angeles realtors, the results were dominated by a handful of luxury names — agents associated with Malibu estates, Beverly Hills listings, and the kind of eight-figure transactions that generate national press coverage. A small number of names affiliated with top-producing teams at major brokerages appeared based on volume rankings that had been covered in trade media. The agents who actually serve the buyers moving at scale — the specialists working Santa Monica, Silver Lake, Echo Park, Los Feliz, Culver City, and the Valley neighborhoods where the vast majority of LA real estate activity occurs — were almost entirely absent from results.

The Silver Lake agent who has closed 40 transactions in the last two years is invisible in AI results. The Echo Park specialist who knows every building on every street doesn’t show up. The Valley agent who serves the SF tech transplants landing in Sherman Oaks — a buyer cohort that is extremely AI-native and researches agents thoroughly before making contact — isn’t in results either. These are active, producing agents with genuine expertise in the markets where LA’s buyers are actually buying. AI doesn’t know they exist.

For LA-specific context on which buyer profiles are searching AI and what signals drive the results, see the Los Angeles market overview.

New York City and Los Angeles are two completely different markets — different price points, different geographies, different buyer cultures. But the agents who appeared in ChatGPT results across both cities had built the same underlying structure. 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 NYC, that meant coverage in The New York Times, The Real Deal, and national luxury rankings. In LA, it meant Los Angeles Times features, national real estate trade coverage, and entertainment industry press that incidentally mentioned real estate transactions. The agents who showed up had been cited by name in sources AI has indexed and treats as authoritative. Their sales volume, their client reviews, their social following — none of those signals are readable by the model. Published citations in trusted third-party sources are.
• 2.Consistent, complete profiles on authoritative aggregators — Full bios on Zillow, Realtor.com, and Google Business describing their specialty, market coverage, and experience in specific, parseable language. AI builds confidence in a name by finding it consistently described across multiple independent sources. The visible agents had complete, keyword-rich profiles that triangulated across platforms. The invisible agents — even those with exceptional production records — often had sparse or generic profiles that gave AI nothing to parse.
• 3.Not: social media reach, website quality, or review count — We checked. Agents with large Instagram followings, polished websites, and hundreds of five-star reviews were no more likely to appear in AI results than agents with minimal online presence. This is the part that surprises most realtors: AI search is a different game entirely. It rewards a specific kind of documentation — published, indexed, third-party citations — that most agents have never focused on building because it never mattered before. It matters now.

In both NYC and LA, the AI visibility landscape is still very early. Most of the agents showing up got there by accident — press coverage they didn’t plan for, rankings they didn’t know AI was reading. In the outer boroughs of New York and the mid-tier neighborhoods of Los Angeles, there is almost no competition for the AI recommendation at all. The first agents to build a deliberate citation presence in those markets will own it. If you want to know where you stand right now, run this 2-minute test to check whether ChatGPT can find you.