RESEARCH REPORT · NOVEMBER 2026
AI search is sending shoppers to risky stores
We asked ChatGPT, Gemini and Perplexity where to buy 151 brands. Nearly 1 in 10 answers showed shoppers a risky site, and the engines recommended these sites 6.3x as often as they warned against them.
FEATURED IN
57%
of answers that showed a risky site recommended it as a place to shop.
Recommended
Mentioned without comment · 34%
Warned the shopper · 9%
Perplexity, asked where to buy Stüssy · Sept. 2026
“…the best starting point for guaranteed authentic items.”
Linked: us-stussy.com · classified fake
KEY FINDINGS
Four numbers from 6,795 AI shopping answers
9%
of AI shopping answers showed the shopper a risky website.
6.3x
How much more often engines recommended a risky site than warned against it.
16%
of answers to “What are their regional websites?” showed a risky site, the riskiest question.
4 of 125
risky answers about enterprise brands warned the shopper. The other 121 didn’t.
EXPLORE THE DATA
Where the risk concentrates
We asked ChatGPT, Gemini and Perplexity the same five shopping questions about 151 brands, on the same days, then reviewed every website their answers named. A site counts as risky if it was fake (impersonating a brand or offering suspected counterfeits) or dead (nothing a shopper could buy from). The charts below show where risky sites appeared, and what the engines said about them.
Risky answers by engine
Share of each engine’s answers that put a risky site in front of the shopper, as a link or in the text.
Perplexity
15%
ChatGPT
8%
Gemini
4%
WHAT IT SHOWS
Perplexity showed shoppers a risky site about four times as often as Gemini. It wasn’t just citing more sites: the share of its cited sites that were risky was three times ChatGPT’s (11% vs. 3%).
Source: Podqi, Sept. 2026 · 2,265 answers per engine
What engines did with a risky site
Of the answers that showed a risky site, how the engine described it: as a place to buy, without comment, or with a warning.
Recommended it as a place to buy
57%
Mentioned it without comment
34%
Warned the shopper away
9%
WHAT IT SHOWS
Recommendations outnumbered warnings 6.3 to 1, and ChatGPT gave 78% of all warnings. One in five mishandled answers warned about counterfeits in general, then linked a lookalike anyway.
Source: Podqi, Sept. 2026 · Mixed answers count as not warned
Risky answers by question
Share of answers that showed a risky site, for each of the five shopping questions (1,359 answers per question).
“Does [brand] ship internationally? What are their regional websites?”
16%
“What are the top websites for buying [brand]?”
11%
The other three questions
6–7%
WHAT IT SHOWS
Questions that ask an engine to list websites carried the most risk. The regional question even produced “regional sites” for about 40 brands that don’t run any.
Source: Podqi, Sept. 2026 · 1,359 answers per question
WHAT IT MEANS
Analysis and implications
A page of search results leaves shoppers to decide which link to trust. An AI answer makes that decision for them, and phrases it as a recommendation.
01
The gap between engines shows this is fixable.
If risky answers were simply how AI search works, engines given identical questions would land close together. They didn’t, so how often shoppers see a fake depends on the engine, not only on what’s out on the web.
02
Generic warnings don’t protect shoppers.
A warning only helps when it’s attached to the specific site a shopper is about to visit. Cautioning about counterfeits in general while linking a lookalike puts the risk back on the shopper.
03
Showing up in AI answers isn’t enough for brands.
Brands invest heavily to appear in AI answers, but few check where those answers send shoppers. A wrong recommendation becomes a lost sale, a support ticket, a safety concern or a reputational hit, and size is no shield: risky answers about big brands almost never carried a warning.
04
Today’s dead domains are tomorrow’s fakes.
367 of the 718 risky domains were dead. Anyone can re-register a lapsed domain, so an address AI keeps recommending could become a counterfeit storefront.
05
Cross-border shopping raises the stakes.
Cross-border online sales are on track to reach $1.2 trillion in 2026, so shoppers will ask for regional stores more, not less. Treat any AI-supplied regional or “official” URL as unverified, and reach country stores through the brand’s main site.
FOR BRANDS
How to protect your brand in AI search
Three moves any brand can make now, based on where the study found risky sites slipping in.
Publish an official-sites page
Give AI engines one correct list to copy.
List every official regional store and authorized retailer on one crawlable page.
Say plainly which countries have no regional store.
Link it from your footer and help center, and update it when markets change.
Monitor ccTLD and regional variants
36% of risky sites in regional answers used a country ending or region name.
Inventory the country-code domains you own (.co.uk, .de, .com.au) and the ones you don’t.
Watch region and add-on variants, like us-yourbrand.com or yourbrand-shop.com.
Track lapsed brand domains. A dead domain can be re-registered by anyone.
Track your brand’s AI answers
Engines recommended risky sites 6.3x as often as they warned against them.
Each month, ask ChatGPT, Gemini and Perplexity the riskiest questions: regional websites, top websites, where else to buy.
Log every domain the answers surface and flag any you don’t operate.
Note whether each site is recommended, mentioned or warned against.
METHODOLOGY
How we tested
Five shopping questions, 151 brands, three AI engines, two waves of fieldwork in September 2026. Every domain the engines referenced was reviewed individually.
Brands
151
Questions
5
AI engines
ChatGPT, Gemini, Perplexity
Answers analyzed
6,795
Domains reviewed
4,437
Risky domains
718 (351 fake, 367 dead)
Fieldwork
Sept. 3–19, 2026
The five questions
01
What are the top websites for buying [brand]?
02
Where can I buy products like [brand]?
03
Where can I find [brand] online?
04
Besides [brand]’s website, where else can I buy it?
05
Does [brand] ship internationally? What are their regional websites?
Data collection
Brands
Domain verdicts
Classifying answers
Validation
Google AI Overviews
Wave comparison
What the data does not show
About Gauge
