AI business recommendations depend on the customer's request, the information available to the particular assistant and how that product generates its answer. Search-enabled assistants can retrieve current web information and combine it into a shortlist, but there is no public, shared scoring formula that tells a Dubai business exactly why it will be selected across ChatGPT, Gemini and Perplexity.
The useful distinction is between what the answer shows, what its sources support and what remains unknown. A confident recommendation can contain accurate details, unsupported claims or outdated information. Being included is therefore worth investigating, not simply celebrating as an endorsement.
The question changes what a suitable business looks like
Consider these hypothetical requests:
“Recommend a coworking space in Dubai.”
“Recommend a coworking space near a Metro station in JLT where I can book a private meeting room for client calls.”
The second request adds constraints. A business suitable for the first may not satisfy the second. Price, location, room access, booking conditions and the distinction between a shared desk and a private room now matter to the customer's decision.
The conversation can add further context. Someone may have already explained that they need Arabic-speaking reception staff or a space for a visiting team. Comparing that answer with a fresh, broad query is not a like-for-like comparison.
OpenAI documents that ChatGPT Search can rewrite a request into targeted queries and may use relevant saved memories when enabled. Approximate location can also shape local results; device location sharing is optional. These are documented context inputs, not a disclosed formula for scoring Dubai companies. How ChatGPT Search works.
This is why “near me” and “in Dubai” should not be treated as identical. The former depends on what location context the product has; the latter explicitly names a city but still leaves many possible neighbourhoods and needs.
Search and answer generation are different parts of the task
A useful way to understand a search-enabled recommendation is to separate three questions:
- What does this customer appear to need?
- What relevant information is available to the system in this interaction?
- What options and explanation does the generated answer present?
This is an explanatory framework, not a claim that every assistant follows an identical internal sequence.
For example, Perplexity describes its consumer search process as interpreting a question, searching online, summarising information and linking sources. Perplexity's process explanation. ChatGPT can use web search, but you should not assume that every response performed a fresh search. A product name alone does not establish the tools or context used in a particular answer.
Likewise, the Gemini app, Google AI Mode and Google AI Overviews should not be combined into one “Google AI ranking”. They are different experiences. Record the actual surface when investigating an answer.
Different sources can answer different questions
A business website can establish what the company currently offers. A directory can help identify a company or branch. A customer review can describe that reviewer's experience. An editorial comparison can explain a writer's shortlist and criteria.
Those are different evidential roles. They do not form a universal ranking order in which one type always outweighs another.
For a Dubai coworking space, the official booking page may be the best place to check meeting-room conditions. A customer review may describe noise during a particular visit. A directory may list an address. None automatically proves all the others, and a page can be accurate about location while wrong about current availability.
Repeated information also needs care. Five websites copying the same announcement do not represent five independent checks of the business. A genuinely independent review can still be old or inaccurate. The task is to assess what the evidence supports, not merely count how many times the company name appears.
A citation does not reveal the whole selection process
Suppose an assistant produces this invented example, using a fictional company:
Harbour Desk is a good option for private client meetings in JLT, with meeting rooms available to day-pass users.
Imagine that the attached link points to a directory entry giving only the company's name, address and a broad “coworking” category. There are three separate conclusions:
| Evidence level | What can be said about this example |
|---|---|
| Visible in the answer | The fictional business was recommended, and the answer made a claim about meeting-room access. |
| Supported by the opened directory | The source identifies a coworking business and its listed location. It does not establish the day-pass conditions. |
| Not established | Whether the room-access claim is current, whether the business fits the full request, or why the assistant selected it over another provider. |
The answer might contain a true fact unsupported by that particular source, or it might contain an error. The citation alone does not resolve the question. Check the relevant current business information before accepting the claim.
Also distinguish a citation to a directory from a citation to the business's own website. The directory may receive the link even though the company receives the recommendation.
Platform interfaces add another complication. Google says Gemini may show sources and related content, and not every answer includes links. A related link is not automatically evidence that the linked page determined the recommendation. Gemini's sources guidance.
Why two answers can contain different businesses
Before attributing a change to a ranking update or a competitor's campaign, check whether the comparison itself changed:
- Was the question broader, narrower or phrased in another language?
- Did one conversation contain previous requirements or name a business?
- Was the same product and search mode used?
- Did the location context differ?
- Were the answers collected on different dates, when offers or available web information could have changed?
These are possible differences to investigate. They do not prove which one caused the changed answer.
An English shortlist does not establish Arabic visibility. A broad Dubai answer does not prove suitability for a particular branch or service area. A company appearing first in a generated list does not, by itself, establish a published quality ranking or a stable number-one position.
The reverse matters too: an omission does not prove that the company is unqualified, unknown to the assistant or technically blocked. Several explanations may fit the same observation.
Do not treat the assistant's explanation as an internal audit
Asking “Why did you recommend this company?” may produce a useful explanation to examine. It is not an authenticated record of all the system's internal decisions.
Google explicitly warns that Gemini can misdescribe how it works, including how it cites sources or supplies fresh information. Gemini's response limitations. Treat an assistant's claimed reasons as statements to verify, rather than accepting them as a hidden ranking formula.
The same evidential discipline should apply to agency reports. “This answer links an old directory” is observable. “That directory caused your competitor to win because reviews have a particular algorithmic weight” requires evidence the answer alone does not provide.
What this means for your Dubai business
Investigate recommendations around the service and customer need that matter to you. Check whether the answer describes the business accurately, whether the linked evidence supports the claim and whether the customer can verify the offer before enquiring.
Correct what you can establish is wrong. Improve missing public facts that matter to a real buying decision. Keep uncertainty about selection separate from known problems in your business information.
Lunasol's Dubai GEO service combines monitoring of relevant recommendations with work on content and online presence. Ask for reporting that separates observed answers, verified source gaps and proposed improvements. That gives you a defensible basis for action without pretending anyone outside the platform can inspect every reason behind its choices.