Ask three AI engines who's best in Dubai: the overlap is low, not zero

We asked ChatGPT, Perplexity and Gemini the same “best in Dubai” question across seven categories on the same day. Between them they named 147 businesses. Ten appeared on all three engines. In three of the seven categories, not one business made all three lists.

The overlap is low, but it isn’t zero, and where it exists it has a cause: a ranking body or a body of trade press that all three engines read. The bigger surprise was inside each engine. ChatGPT asked the same question minutes apart named the same clinic first both times, then a different set of clinics below it.

For a Dubai business, the practical point is that a visibility score from one engine on one run tells you about that engine on that run. It won’t tell you what the other engines say, or what the same engine says next time.

This is the second of three pieces from our September test. Piece 1 covers companies writing the articles AI quotes about them. Piece 3 covers what each engine reads before it answers.

What did we test?

We asked ChatGPT, Perplexity, Gemini and Google Search “Best [category] in Dubai” across seven categories: law firms, B2B SaaS, aesthetic clinics, boutique hotels, industrial manufacturers, universities and car dealerships. All logged out, free tier, UAE location, 44 answers in total. Clinics and manufacturers were run three times on every surface. The overlap figures below compare the three chat engines; Google’s AI Overview appeared on four of the seven categories, so it’s covered separately.

How often do the AI engines name the same businesses?

We counted every business an engine recommended, including “also worth considering” lists and separate tiers, and excluded passing mentions in caveats. For clinics and manufacturers we pooled the three runs on each engine.

Category	Businesses named across the three engines	ChatGPT and Perplexity	ChatGPT and Gemini	Perplexity and Gemini	On all three
Law firms	24	2	4	4	0
B2B SaaS	18	5	3	6	3
Aesthetic clinics	25	2	1	3	0
Boutique hotels	14	3	1	1	1
Industrial manufacturers	34	2	2	5	2
Universities	14	6	6	7	4
Car dealerships	18	1	6	2	0
Total	147				10

The ten businesses on all three engines:

Category	On ChatGPT, Perplexity and Gemini
Universities	American University in Dubai, Canadian University Dubai, University of Wollongong in Dubai, University of Dubai
B2B SaaS	Bayzat, GrubTech, Dukkantek (DTEK)
Industrial manufacturers	Emirates Global Aluminium (EGA), Ducab
Boutique hotels	Beach Walk Boutique Hotel

About 7% of the businesses named made every list. A business can lead one engine and be missing from another, and in law firms, clinics and dealerships that was true of every business named.

Why do Perplexity and ChatGPT disagree?

They read different things. In almost every category, Perplexity grounded its answer on editorial coverage and ChatGPT grounded its answer on listings and directories.

	Sources it leaned on
Perplexity	GRAZIA, Country & Town House, What’s On, Upgraded Points, Manufacturing Digital, Legal 500
ChatGPT	Bayut, Best in Hood, Doctify, Dubai Industrial City, dubicars.com

Industrial manufacturers show it most clearly. Across three runs each, ChatGPT’s shortlist was SME fabricators: Al Shirawi, SIGMA, NOVA Composites, CAMTECH, Johar, Hotpack. Perplexity’s was heavy industry: EGA, Ducab, Jebel Ali Cement, Jubaili Bros, All Metals, Invention Steel. EGA and Ducab were the only names on both, and on ChatGPT they sat in a separate “large companies” section rather than the shortlist. The two engines didn’t share a single source either. ChatGPT cited Bayut, Dubai Industrial City, Dubai Holding, Dubai Investments and ICD. Perplexity cited mazeed, UAE Business Blog and Manufacturing Digital.

ChatGPT, logged out, UAE. SME fabricators in the shortlist, heavy industry set apart. Recaptured for publication; the shortlist differs from the logged runs, which is the next section’s point.

Same prompt, two readings of what a “manufacturer” is. Gemini sided with Perplexity: it shared five manufacturers with Perplexity and two with ChatGPT.

Does the same engine give the same answer twice?

Not below first place. We ran ChatGPT’s aesthetic clinics answer three times, minutes apart.

Position	Run 1	Run 2	Run 3
1	Biolite Clinic Dubai	Biolite Clinic Dubai	Biolite Clinic Dubai
2	Los Angeles Aesthetic Medical Center	Glow Aesthetics Dermatology Clinic	CLINICA Cosmetic Poly Clinic
3	CLINICA Cosmetic Poly Clinic	Los Angeles Aesthetic Medical Center	New Me Clinic
4	Athena Dermatology Clinic	Athena Dermatology Clinic	Five Cosmetic
5	EDEN Aesthetics Clinic	Modern Aestheticss Dermatology & Laser Clinic	Athena Dermatology Clinic
6	Five Cosmetic	—	Premium Cosmetic Laser Center

Biolite was first every time. Athena was the only other clinic in all three runs. Ten different clinics filled 17 slots.

The engines don’t all vary the same amount:

Engine	Category	Same #1 in all three runs?	In every run	Different businesses named
ChatGPT	Clinics	Yes (Biolite)	2	10
ChatGPT	Manufacturers	No (Al Shirawi twice, SIGMA once)	4	9
Perplexity	Clinics	No (Hortman once, another clinic twice)	5	14
Perplexity	Manufacturers	Yes (EGA)	7	11
Gemini	Clinics	Yes (Hortman)	2	7
Gemini	Manufacturers	Yes (EGA)	4	11

Gemini’s clinic answer was the steadiest: Hortman first and The Nova second in every run. Google’s own results page didn’t move at all. The organic results and local pack were identical across three runs; only the AI layer varied.

What happens when one business goes by two names?

The engines split it. One Dubai aesthetic clinic in our results trades under two spellings of its name, which we’ll call Name A and Name B. Each surface settled on a different version.

Surface	How it named the clinic
Google Search	Name A, in the local pack and via its own site in organic results
Perplexity	Both names in one entry, ranked first in two of three runs
Gemini	Name B only, in one of three runs
ChatGPT	Name B only, as a passing mention in one of three runs

Perplexity was the only engine to connect the two names, and it ranked the clinic first. Google shows one name, the other two AI engines show the other.

A business with inconsistent naming gives each engine a chance to treat it as someone else, or to pick up only part of its reputation. The fix is practical: one canonical name across the website, Google Business Profile and directory listings, with the alternate spelling declared in structured data so every engine resolves to the same record.

Where do the engines agree, and why?

Where all three read the same kind of authority. Universities had the most overlap, with four institutions on all three engines, and it’s the category where independent rankings (Times Higher Education, QS, uniRank) are everywhere in the sources. B2B SaaS came next, with trade coverage like eChai Ventures shared across engines.

Car dealerships showed a different pattern. ChatGPT and Perplexity shared one dealer, Gargash. Gemini shared six with ChatGPT (including ALBA CARS, The Elite Cars and the franchise groups) and two with Perplexity (Al Tayer Motors, F1rst Motors). Gemini sat between the two engines that otherwise barely overlapped.

Google’s AI Overview mostly picked from the same consensus names:

Category	Named in the AI Overview	Also named by
Industrial manufacturers	Ducab, EGA	All three engines
Industrial manufacturers	NAFFCO	Gemini
Universities	Canadian University Dubai	All three engines
Universities	University of Birmingham Dubai	Perplexity, Gemini
Law firms	Al Tamimi & Company, Hadef & Partners	ChatGPT, Gemini
Law firms	Clyde & Co	Perplexity, Gemini
B2B SaaS	Dukkantek (DTEK)	All three engines

In manufacturers, universities and law firms, every business the AI Overview named was on at least one of the three engines, and most were on two or more. B2B SaaS is the partial exception: of the three companies its AI Overview led with, only Dukkantek made all three engines. Nazm.ae and Verofax did not.

What does a single-engine, single-run score miss?

Most of the picture. A score taken from one engine once can’t show:

What it misses	Evidence from this test
The other engines	10 of 147 businesses named appeared on all three
The next run	ChatGPT named 10 different clinics across three runs of the same prompt
Which source to fix	Perplexity reads editorial, ChatGPT reads listings
Naming splits	One clinic appeared under one spelling on Google and another on Gemini and ChatGPT

Even the most anchored category reorders. ChatGPT’s law firm answer was grounded entirely on Legal 500 in both our August scan and in September. Between the two, A&O Shearman went from first to absent, Dentons and Norton Rose Fulbright dropped out, King & Spalding came in, and Al Tamimi moved from fourth to first. A directory holds the source steady. It doesn’t hold the ranking steady.

Methodology

• Prompt: “Best [category] in Dubai”, one prompt shape, English only.
• Categories: law firms, B2B SaaS, aesthetic clinics, boutique hotels, industrial manufacturers, universities, car dealerships.
• Surfaces: ChatGPT, Perplexity, Gemini, Google Search.
• Conditions: data collected 10 September 2026. Four surfaces, logged out, clean profile, geo verified to the United Arab Emirates, free or default model tier. Fresh session per cell. Signed-out Gemini served Flash-Lite.
• Volume: 44 answers. Clinics and manufacturers ran three times on every surface (n=3); the other five categories ran once (n=1). Single-run categories may overlap more or less on a repeat, and the n=3 categories have larger pooled lists, which lowers their overlap share.
• Overlap counting: every business recommended, including “also consider” lists and separate tiers; passing mentions in caveats excluded; Perplexity counted from its written answer, not its Places module. One Perplexity hotel entry was truncated in our log, so hotel overlap may be slightly understated.
• Market: Dubai only.
• Date: re-run logged 10 September 2026. The law firm comparison uses the ChatGPT cells from our August scan, which were logged out on the same conditions as September.
• What this doesn’t cover: signed-in or paid tiers, other phrasings, Arabic queries, Claude and Copilot.
• Screenshots: recaptured after the logged run. Answers shift between runs, so every number here comes from the run log.

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