cargrid research · June 2026
AI plays favorites. Your dealership probably isn’t one.
35 cities. Three countries. We asked ChatGPT the questions buyers ask before they choose a dealer — and recorded every name it gave back. The results surprised us.
Before we dive in · The landscape
Car buyers are already asking AI where to shop.
Before we ran a single query of our own, we reviewed the major 2025–2026 studies on how car buyers use AI — from Cox Automotive, Cars.com, CarGurus, CarEdge and Ekho. Across tens of thousands of surveyed shoppers, three things are now clear.
Buyers already use AI.
- 19% of all car buyers — and 25% of new-vehicle buyers — used AI tools while shopping, the first year the study tracked it. — Cox Automotive, 16th Annual Car Buyer Journey Study, Jan 2026 · n=2,300
- 30% of active shoppers used generative AI during research — and ChatGPT accounted for 68% of that use. — Ekho 2026 AI Vehicle Research Study · n=627
- 40% of in-market buyers expect to use AI next time, up from 14% of recent buyers. — CarEdge, 2025 · n=500
Act on what AI says.
- 41% of shoppers say they're most likely to visit the dealer or brand an AI recommendation names. — Cars.com AI in Car Shopping Survey, Nov 2025 · n=936
- 40% use AI to find listings; 36% use it to check dealership reviews. — CarGurus 2025 Consumer Insights Report · n>3,000
- 44% have already used AI-powered search tools on car marketplaces. — Cars.com, Nov 2025
Trust what AI tells them.
- 97% of AI users say it will impact their purchase decision; 71% already place at least moderate trust in it. — Cars.com, Nov 2025
- 59% of AI users reported high satisfaction with the help they received. — Cox Automotive, Jan 2026
- 83% of consumers believe AI will reshape how cars are bought. — Cox Automotive, Jan 2026
Every one of these studies agrees buyers are turning to AI to decide where to shop — and acting on what it says. But none of them asked the obvious next question: when a buyer does, which dealers does AI actually name?
Our method
So we ran the test ourselves.
We wanted to see exactly what a buyer sees when they turn to AI at the start of their search — before they visit a lot, before they fill out a lead form, before they even open Google Maps. We asked the same three questions real buyers ask, in 35 cities across three countries, and recorded every name ChatGPT gave back.
The 3 questions, asked in every city
- 1“What are the best car dealerships in my city?”
- 2“Where can I find an SUV under $30,000 near my city?”
- 3“Where can I get the best financing or bad credit car loan near my city?”
The results
Here’s what we found.
AI doesn’t show a list of your local options — it names just a handful, and they’re overwhelmingly big franchise groups and national marketplaces. The local dealer is mostly absent. And which names make the cut shifts with what the buyer asks — three questions, three different sets of winners.
And here’s who fills them
Each dot is 1 in 10 dealers. If you’re not one of the few AI names, you’re not in the running — and about 9 in 10 aren’t.
“Not named” = absent from ChatGPT’s first answer to these 3 questions, measured against the modeled dealer count per market.
What the data shows
And it crowns the incumbents.
A franchise dealer takes the #1 spot in 32 of 35 cities. A local independent led in just one — Bristol — and only on the back of standout local reviews. The single-rooftop store isn’t competing on a level field; it’s competing against brand memory.
The game changes by country.
How hard AI leans on big franchise dealers — and who fills the rest of the shelf — depends on where you operate. In the US it’s a franchise game; in Germany the marketplaces (mobile.de, AutoScout24) take roughly a third of every answer; in the UK independents have their best shot anywhere in the study.
And your highest-intent buyer? AI sends them to a lender.
When buyers asked about financing and bad credit, AI named a real local dealer first only 29% of the time. The rest went to credit unions, lenders, and brokers. The shopper who’s ready to sign — your most valuable lead — is the one AI most often hands to someone else.
Sometimes AI names no dealer at all. In several cities the safest answer wasn't a store but an instruction — “use Cars.com and filter by price and distance.” That turns AI from a recommender into a lead funnel for the marketplaces.
In Germany, “bad credit” makes AI cautious. German bad-credit wording (around SCHUFA) pushed assistants toward portals and specialist “ohne Schufa” providers instead of mainstream franchise dealers.
In the UK, a broker usually beats the dealer to the buyer. Finance queries favored Auto Trader, CarFinance 247 and Zuto/Oodle-style brokers — leaving the dealer as inventory fulfillment after the finance relationship is captured elsewhere.
Curious where your store lands on these questions? Get your free report →
Find your market
Is your dealership on the list?
Scroll to your market — or the one nearest you — and see who AI recommends when buyers ask about the best dealership, an SUV under budget, and bad-credit financing.
Each list is a combined ranking across all three questions — who AI surfaced most often overall in that market, not a separate result for each question. The % franchise is the share of those recommendations that went to big franchise dealers.
United States
69% franchiseAtlanta, GA
73% franchiseAtlanta is group-led: Nalley, Jim Ellis, Hennessy, and Ed Voyles are memorable to AI, while Hola appears only in the bad-credit lane.
Boston, MA
70% franchiseHerb Chambers is the dominant entity; smaller Boston used lots surface mainly when the prompt asks about low-budget or credit-challenged buyers.
Charlotte, NC
65% franchiseHendrick’s hometown authority dominates, but used-car and credit-specialist brands still capture late-funnel shoppers.
Chicago, IL
57% franchiseChicago’s answer set is split between reputable franchise stores and finance-specialist used dealers that match the bad-credit wording.
Columbus, OH
72% franchiseColumbus is a dealer-group memory market: Germain, Ricart, Lindsay, and Byers crowd out most smaller lots.
Dallas, TX
72% franchiseDallas rewards premium franchise authority, but financing intent often names RoadLoans or pre-approval paths before any local rooftop.
Denver, CO
73% franchiseDenver’s answers favor franchise authority for discovery, but Queen Auto Sales and similar independents surface when credit wording is explicit.
Detroit, MI
45% franchiseDetroit’s bad-credit prompt strongly pulls in independent used lots, lowering franchise share despite the city’s OEM heritage.
Houston, TX
72% franchiseLarge franchise groups win discovery, but bad-credit financing introduces independent operators such as Fleet Nation and EZ Keys into the answer.
Indianapolis, IN
74% franchiseIndianapolis has lower invisibility than major metros, but most AI recall still concentrates in four large groups plus one BHPH operator.
Kansas City, MO
70% franchiseAI bridges both sides of the state line and tends to name recognizable brand stores plus Auto Bank for bad-credit intent.
Los Angeles, CA
71% franchiseGalpin and LAcarGUY have strong entity authority, but the SUV-under-budget prompt quickly shifts attention to Autotrader and car supermarkets.
Miami, FL
68% franchiseMiami’s AI answers favor Toyota/Honda franchise anchors for trust, then hand price-constrained SUV discovery to CarGurus or HGreg-style inventory aggregators.
Minneapolis, MN
73% franchiseDealer groups with broad Twin Cities footprints are easy for AI to remember, while CarHop appears as the explicit bad-credit alternative.
Nashville, TN
68% franchiseNashville’s AI set spans in-city franchise dealers and Franklin-area rooftops; Stars Auto Finance appears only for credit-challenged queries.
New York, NY
56% franchiseAI compresses the huge NYC dealer universe into a few high-authority Queens/Bronx/Manhattan names plus portals; most borough independents never appear.
Orlando, FL
71% franchiseOrlando’s price-sensitive SUV prompt is highly portalized, while Credit Cars has a clear niche in bad-credit answers.
Philadelphia, PA
55% franchiseFranchise visibility is diluted by strong used-car and portal answers; Naryan appears because it matches used-car and financing intent closely.
Phoenix, AZ
70% franchiseCamelback’s multi-brand footprint gives it repeated AI recall across discovery and SUV searches, while DriveTime absorbs subprime finance attention.
Portland, OR
74% franchisePortland franchise stores retain discovery authority, but the financing prompt pulls in Seaport Auto, Atlas-style finance pages, and Autotrader filters.
Salt Lake City, UT
75% franchiseSalt Lake City has unusually strong local dealer-group recall, especially Mark Miller, Ken Garff, and Larry H. Miller.
San Antonio, TX
73% franchiseGunn, North Park, Jordan, and Ancira are memorable franchise names, but Chacon wins direct subprime relevance.
San Francisco, CA
75% franchiseAI tends to expand from San Francisco proper into Daly City and Serramonte because the city has fewer large in-city rooftops than the Bay Area overall.
Seattle, WA
76% franchiseSeattle’s dealer answers cluster around a few recognizable in-city rooftops; Pierre Money Mart wins unusual visibility on bad-credit wording.
Tampa, FL
75% franchiseTampa’s franchise share is high because several local stores publish explicit financing pages, but Autotrader remains the SUV filter default.
Germany
52% franchiseBerlin, Germany
55% franchiseBerlin’s scale produces severe invisibility; Autohaus König and Dinnebier are memorable, but mobile.de and AutoScout24 dominate SUV discovery.
Cologne, Germany
51% franchiseCologne has better mid-market dealer visibility than Berlin, but AutoScout24 and mobile.de still siphon the high-intent SUV prompt.
Frankfurt, Germany
55% franchiseFrankfurt combines strong regional franchise groups with finance-oriented used dealers; SCHUFA wording shifts visibility away from OEM rooftops.
Hamburg, Germany
54% franchiseHamburg’s established Autohaus brands show up for trust, but portals remain the assistant’s safest answer for 30.000-€ SUV inventory.
Munich, Germany
45% franchiseMunich AI answers over-index on MAHAG for franchise trust, but independent used dealers and portals capture budget-SUV and financing intent.
United Kingdom
46% franchiseBirmingham, UK
54% franchiseBirmingham’s local reputation concerns make AI more cautious, so franchise and Auto Trader recommendations are framed as safer than small-lot shopping.
Bristol, UK
36% franchiseBristol’s answer set is used-car-heavy; Autochoice and Carbase appear more often than franchise stores, while Compass-style brokers capture bad-credit finance.
Glasgow, UK
50% franchiseGlasgow is one of the few cities where a local-origin dealer group, Arnold Clark, can compete with Auto Trader for top AI recall.
London, UK
42% franchiseLondon is the most portalized UK market: Auto Trader and car supermarkets often appear before individual franchise rooftops.
Manchester, UK
48% franchiseManchester AI answers lean national: Auto Trader, CarShop, and finance brokers compete directly with Arnold Clark, Lookers, and Williams.
Don’t see your store on your city’s list? Find out exactly where you stand — on the questions real buyers ask, in your market.
Get your free reportWhy this is happening
It isn’t one race. It’s three.
Across the study, each of the three questions surfaces a different set of winners — which is why a dealer can own one and never appear in the others. AI isn’t running a single race for “best dealer.” It’s running three.
“What are the best car dealerships in my city?”
Big franchise groups win.
“Where's an SUV under $30,000 near me?”
The marketplaces win.
“Where can I get a bad-credit car loan?”
Lenders & specialists win.
The financing lane is the one place independents and specialists routinely beat the big groups — proof the shelf is earnable, one question at a time.
The opportunity
You don’t have to win every race — just yours.
Because the market is intent-segmented, you don’t need to outrank a national group on everything. You need to be the clearest, best-documented answer to the questions you already specialize in — used SUVs, bad-credit financing, a specific brand. That’s a race you can win, and the dealers AI names all do three things to win it.
Structured, crawlable inventory
AI can only recommend stock it can read — VIN-level pages, prices, body styles, distance, no blocked crawlers.
Real financing content
A genuine bad-credit / first-time-buyer page beats a generic finance center — and it's where independents actually win a spot.
Review authority
Consistent ratings across Google, the marketplaces and OEM directories is what AI leans on to trust a name enough to say it.
Want to roll up your sleeves? Our 5-minute AI visibility audit walks through how to check what AI says about your store and start fixing it yourself. But the first move is the same either way — knowing exactly where you stand today, on every question that matters.
This study asked 3 questions. Your free report asks dozens — about your store.
We go deep on one dealership: testing the real questions your buyers ask across every category you compete in — discovery, used inventory, financing, service, your brands — and showing you which races you’re already winning, which you’re losing to a marketplace or a bigger group, and exactly what it takes to climb.
See where your store can winFree · personalized to your dealership · delivered within 24 hours
- “What are the best car dealerships in my city?”
- “Where can I find an SUV under $30,000 near my city?”
- “Where can I get the best financing or bad credit car loan near my city?”
- 35 cities across the US, Germany and the UK
- Model: gpt-5.5 with live web search
- Run June 2026
- Each city’s ranking is combined across all three questions, weighted by how often AI named each business