AI Visibility Index · Off Plan Real Estate

Dubai off-plan: who AI recommends,
and who's invisible.

We put 40 questions a Dubai off-plan buyer actually asks to ChatGPT, Claude, Gemini and Perplexity, and recorded which developers and firms each engine names. 354 names came back - only 35 firms appear on 2 or more engines, and a handful dominate the channel buyers increasingly start with.

354
names extracted from the answers
35
firms named on 2+ engines
40%
top firm's visibility (Emaar)
160
AI answers analysed
AI Engines Queried
ChatGPT
Claude
Perplexity
Gemini
Executive summary

Only 35 of 354 names are firms AI repeatedly recommends

When a Dubai buyer asks AI about off-plan, the same names come back - Emaar, DAMAC, Sobha, Nakheel, Binghatti. Of the 354 distinct names extracted from the answers, only 35 developers and firms are named on 2 or more engines once duplicate name variants are merged and districts, individual projects and other non-firm entities are removed. The rest rarely surface at all.

The leaderboard

The 35 firms AI actually names

Visibility = share of the 160 AI answers naming the firm, with name variants merged before counting (Sobha / Sobha Realty, DAMAC / DAMAC Properties, Nakheel / Nakheel Properties, Danube / Danube Properties, Ellington / Ellington Properties). Only developers and firms named on 2 or more engines are ranked; districts, individual projects and non-firm entities are excluded.

#FirmQuestions (of 40)Answers (of 160)Visibility
1Emaar246440.0%
2DAMAC213421.3%
3Sobha143220.0%
4Nakheel142113.1%
5Binghatti91911.9%
6Engel & Völkers121610.0%
7Meraas121610.0%
8Knight Frank8138.1%
9Betterhomes7127.5%
10Omniyat9116.9%
11Ellington7116.9%
12Select Group795.6%
13fäm Properties595.6%
14H&S Real Estate595.6%
15Metropolitan Premium Properties595.6%
16Azizi685.0%
17Danube485.0%
18Christie's International Real Estate374.4%
19Driven Properties563.8%
20Allsopp & Allsopp463.8%
21Gulf Sotheby's263.8%
22haus & haus353.1%
23Luxhabitat353.1%
24D&B Properties242.5%
25Provident242.5%
26Aeon & Trisl331.9%
27Aldar331.9%
28Dacha Real Estate331.9%
29Nshama331.9%
30Savills331.9%
31White & Co331.9%
32Arada231.9%
33McCone231.9%
34John Taylor221.3%
35Range International221.3%
+ 319 more extracted names sit below the 2-engine bar or outside the firm set. Get the full breakdown & where you rank →

Among the 35 developers and firms AI names on 2+ engines in this probe, the median visibility is 4.4%; the top firm is named in 40% of answers. Districts and master-communities (Dubai Marina, Downtown Dubai, JVC, Dubai Creek Harbour), individual projects and hotel-branded residence lines are excluded from the ranking.

Most recommended

The five names AI returns most

1
Emaar
The most-named developer - 24 of 40 buyer questions, all four engines.
Visibility40%
Answers (of 160)64
2
DAMAC
Named on all four engines, variants merged (DAMAC / DAMAC Properties).
Visibility21%
Answers (of 160)34
3
Sobha
Named on all four engines, variants merged (Sobha / Sobha Realty).
Visibility20%
Answers (of 160)32
4
Nakheel
Named on all four engines - 14 of 40 buyer questions.
Visibility13%
Answers (of 160)21
5
Binghatti
Named on all four engines.
Visibility12%
Answers (of 160)19
The sources

What AI reads to answer

These directories, regulators and platforms surfaced in AI answers. They are not competing for the buyer - they are the third-party sources AI re-reads. Getting listed and well-reviewed on them moves your own visibility.

SourceTypeEngines
bayut.comDirectory1
reddit.comForum1
legalclarity.orgPublication1
immigrationstartguide.comPublication1
gulfnews.comPublication1
+ more sources cited across the cohort. Get the full source list →
How AI builds an answer

An AI answer is built from 6 layers. Most firms cover 1.

When ChatGPT, Claude, Gemini or Perplexity answer a buyer's question, the response is assembled from six technical inputs. No single marketing discipline covers them all - which is why most firms never make the 35 that AI names on 2+ engines.

SEO covers2 of 6
PR covers1 of 6
Content teams cover1 of 6
28 Labs coversall 6
1Crawler access
Can the AI engines read your site at all? Default CMS configs block at least 2 of the 4 AI crawlers.
2Machine-readable structure
Schema, clean markup, clear entities the engines can parse.
3Answer-shaped content
You directly answer the questions buyers ask.
4Authority & citations
Independent sources - directories, regulators, reviews - corroborate you.
5Freshness
The data is current.
6Per-engine presence
You appear across all four engines, not just one.

Get 28 Labs to set you up for success

We cover all six layers - the audit, the fixes, and the ongoing visibility - so AI starts recommending you. One programme, every engine.

Talk to 28 Labs
About

28 Labs - we measure who AI recommends

28 Labs measures how brands get recommended across ChatGPT, Claude, Gemini and Perplexity. We've analysed 11,000+ AI answers covering 100+ brands across 15 markets - a uniquely deep view of what AI actually recommends, and why.

11,000+
AI answers analysed
100+
brands tracked
15
markets
4
AI engines
FAQ

Frequently asked questions

Which developers does AI recommend for Dubai off-plan?

Emaar, DAMAC, Sobha, Nakheel and Binghatti are named most across ChatGPT, Claude, Gemini and Perplexity. In total 35 developers and firms are named on 2 or more engines; the rest of the 354 extracted names rarely surface.

How many Dubai off-plan names does AI actually return?

160 answers surfaced 354 distinct names, but after merging duplicate name variants and removing districts and non-firm entities, only 35 firms are named on 2 or more engines.

What sources does AI read to answer Dubai off-plan questions?

The most-cited sources are bayut.com, reddit.com, legalclarity.org - the third-party pages AI re-reads when it builds an answer.

How is this measured?

40 buyer questions x 4 engines (ChatGPT, Claude, Gemini, Perplexity) = 160 answers, single snapshot dated 2026-06-20, retrieval-enabled probe. Snapshot 1 - June 2026; a second snapshot is planned. Citations reflect the retrieval / web layer; some recommendations draw on training data with no visible citation. Not yet a benchmark.

How this snapshot was built.

Method. 40 buyer questions x 4 engines (ChatGPT, Claude, Gemini, Perplexity) = 160 answers, single snapshot dated 2026-06-20, retrieval-enabled probe. Each developer and firm is scored on whether the engines name it across the questions a Dubai buyer actually asks. "Visibility" = share of the 160 answers naming it, with name variants merged before counting. Citations reflect the retrieval / web layer; some recommendations draw on training data with no visible citation.

Status. Snapshot 1 - June 2026. A second snapshot is planned. Do not quote as a benchmark until it lands.

Press & data requests: [email protected]

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28 Labs · AI Visibility Research · Dubai Off Plan Real Estate AI Visibility Index, June 2026. Describes AI engine behaviour at time of testing; not investment advice.