Does AI Recommend Toronto Real Estate Agents? We Asked ChatGPT, Perplexity, Gemini, and Google

The short version: we asked the four major AI answer engines to recommend a Toronto real estate agent on September 21, 2026. They named specific agents and teams readily, the same small shortlist kept recurring across engines, and they picked them from Google reviews and RankMyAgent, not from real estate portals. Realtor.ca, HouseSigma, and Zolo were essentially absent from the citations. If you are a Toronto agent, that single fact tells you where to invest.

This is the real estate companion to our law firms study, and part of the monthly measurement we run in the Toronto AI citation tracker.

How we tested (and the honest limits)

We queried four surfaces: ChatGPT (logged-out, the public default), Perplexity, Gemini (logged in, with web search), and Google (Canada region). We ran two buyer and seller queries, "best real estate agent in Toronto" and "best realtor for selling a house in Toronto," and logged which agents and teams each engine named and which sources it cited.

The honest caveats, up front. This is a focused field test on a single date with two query types, not a large statistical sample. AI answers shift with phrasing, personalization, location, and time, so each engine names a somewhat different set on a different day. Treat the specific names below as a snapshot of what these engines surfaced, not as a ranking or endorsement. The value is in the pattern, which was strikingly consistent.

Finding 1: AI names specific agents and teams, not brokerages or portals

Every engine named individual agents and teams. For "best real estate agent in Toronto":

• ChatGPT rendered a Google-Maps-style widget with The Storey Team (5.0), Team Asgarian at RE/MAX Hallmark (5.0), and Jenelle Tremblett (5.0, 301 reviews), plus Shay Asnani (5.0, 216 reviews) in the text, citing RankMyAgent and Google reviews.
• Perplexity returned a RankMyAgent table led by the Dave Elfassy Team (4.97, 1,096 reviews), Ina Halko (5.00), and Arun Ganguly (4.98).
• Gemini showed Google place cards for Dave Elfassy Real Estate, the Christine Cowern Real Estate Team, Susan Gucci Realty, and Ina Halko.

Notice what it did not name: the big national brokerage brands as such, and not a single portal listing. It named people.

Finding 2: A small shortlist recurs across every engine

Four names appeared across ChatGPT, Perplexity, and Gemini: the Dave Elfassy Team, the Christine Cowern Real Estate Team, Ina Halko, and Arun Ganguly. When we switched to a selling query, the same teams led again. There is a consensus shortlist, and being on it is the goal. The engines converge on a handful of high-review names rather than surfacing a long tail.

Finding 3: The source that decides it is RankMyAgent, plus Google reviews

The connective tissue was not a portal. It was RankMyAgent, Canada's real estate review platform, cited by both ChatGPT and Perplexity, alongside Google Business Profile reviews (which power the map widgets and place cards in ChatGPT and Gemini) and Rate-My-Agent. Perplexity said it plainly, that its list was based on RankMyAgent's verified reviews. Google reviews and RankMyAgent, together, are the deciding inputs. Review volume is the currency.

Finding 4: Real estate portals get almost nothing

Here is the finding that should change where Toronto agents spend. Across every engine and both queries, Realtor.ca, HouseSigma, and Zolo were essentially absent from the citations. We saw a single Zillow citation, once. This mirrors a 2026 US study (Omni Eclipse) that found AI drew 98 percent of its real estate citations from Google Business Profiles and agent websites, and gave Zillow, Realtor.com, and Redfin zero. In Toronto, the same pattern held. Your portal profile is not what gets you named by an AI. Your reviews are.

Finding 5: Luxury queries surface a different shortlist

Intent changes the answer. For high-end sales, the engines shifted to agents known for record deals: Jane Zhang at Sotheby's International Realty (cited for a $23.5M Forest Hill sale), Chestnut Park (cited for a $32.8M Bridle Path sale), and the Cailey Heaps team at Heaps Estrin. For luxury, the currency is your recent multi-million-dollar closings and brokerage brand, and the engines sourced those from news coverage rather than review counts. So a strong review base wins the mainstream query, and documented record sales win the luxury one.

Finding 6: On Google, there is no AI Overview for "best agent" yet

Unlike the legal queries we tested, "best real estate agent in Toronto" did not trigger a Google AI Overview at all. Google showed sponsored ads and the local pack, with organic results below. So on Google specifically, the local 3-pack and ads still fully own this query. The AI recommendation lives in the standalone assistants, ChatGPT, Perplexity, and Gemini, and not yet in Google's main results for real estate. That is a meaningful difference from law, where an AI Overview did appear.

What this means if you are a Toronto agent

The path to the AI shortlist is unusually concrete for real estate.

1. Build your RankMyAgent reviews. It is the single directory the AI engines lean on for agents. Depth and recency of verified reviews there is the strongest lever you have.
2. Win on Google Business Profile. Ratings and review volume drive the map widgets and place cards in ChatGPT, Gemini, and Google's local pack. This is the other half of the currency.
3. Add Rate-My-Agent. A secondary review platform that also surfaces in AI answers.
4. Do not over-invest in portal profiles for AI visibility. Realtor.ca and HouseSigma matter for buyers browsing listings, but they are not what gets you named by an AI. If AI visibility is the goal, reallocate that effort toward reviews.
5. For luxury, make your record sales public. News coverage of notable closings is what the engines cite for high-end intent, so pitch and publish those.
6. On Google, own the local pack. No AI Overview triggers on "best agent" today, so local SEO, categories, and reviews are the game there.

None of this is about gaming a model. It is about accumulating genuine, verified reviews on the two platforms these engines actually read. If you want to see where your own profile stands, start by checking whether AI can reach and read your site and by auditing your Google Maps presence.

Limitations

This is a focused field test on one date, two query types, and four engines. AI answers shift with phrasing, personalization, location, and time, so the exact agent lists are a snapshot, not a ranking, and your own query may differ. What is stable, and what matters, is the pattern: named agents, a recurring review-built shortlist, RankMyAgent and Google reviews as the deciding sources, and portals almost entirely absent. We measure Toronto AI citations monthly and will keep expanding this.

FAQ

Does ChatGPT recommend specific real estate agents in Toronto? Yes. In our September 2026 test, ChatGPT named specific Toronto agents and teams, usually through a Google Maps place widget with star ratings, citing RankMyAgent and Google reviews.

Does AI use Realtor.ca or HouseSigma to recommend agents? Essentially no. Across every engine and query we tested, Realtor.ca, HouseSigma, and Zolo were absent from the citations (we saw one Zillow reference). The engines relied on Google reviews and RankMyAgent instead.

How do I get my real estate business recommended by AI? Build a deep, current base of verified reviews on RankMyAgent and Google Business Profile, the two sources the engines read for agents. Add Rate-My-Agent, and for luxury, get press coverage of your record sales.

Which review site matters most for real estate AI visibility? RankMyAgent was the single most-cited directory across the AI engines in our test, alongside Google Business Profile reviews.

Does Google show an AI Overview for "best real estate agent in Toronto"? Not in our test. Google returned sponsored ads and the local pack with no AI Overview, so on Google the local 3-pack and ads still own that query. The AI recommendations came from ChatGPT, Perplexity, and Gemini.

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