In the past, patients found a dental clinic mainly by browsing Meituan, scrolling Douyin or asking friends.
Now more and more people open Doubao or DeepSeek and ask directly, "Which dental clinics nearby are worth looking into?" or "How do I choose dental implants?" The AI generates an answer recommending a few clinics, and the patient then opens a platform to book.
How big is this change? The CNNIC 57th Statistical Report on China's Internet Development shows that by December 2025, China had 602 million generative AI users, a penetration rate of 42.8%. More than four in every ten internet users are using AI tools, and a considerable share of them now treat "asking AI" as the first step in choosing a clinic.
If your clinic is not in the AI's answer, these new patients have nothing to do with your clinic.
The way clinics win patients has already changed.
Three entry points with completely different logic
| Entry point | What the user does | How it works and what it costs |
|---|---|---|
| Traditional search (Baidu) | Searches keywords, looks at rankings | Rankings can be optimised, but bidding is fierce and costs keep rising |
| Platform operations (Meituan / Douyin) | Browses stores, compares group-buying offers, checks ratings | The store can be operated, but depends on platform rules; costs are commission plus paid promotion |
| AI search (Doubao / DeepSeek) | Asks directly "which one is good?" and the AI recommends | Relies on information assets plus source endorsement; mainly content and source deployment |
These do not replace one another; they stack. Patients first ask AI to draw up a shortlist, then compare and book on a platform. Platform operations decide whether you can be seen in the store listings; AI search decides whether you get onto the shortlist at all.
Why would AI recommend you? Three switches you can check
When AI answers "which dental clinic is good?", it does not name clinics at random. It judges on three things.
Switch one: consistent information — does AI see you as one entity?
Your clinic's name, address, phone number, dentists, treatments and prices must be exactly the same on your website, Meituan, Douyin, news sources and Q&A communities. Is the name "XX Dental" or "XX Dental Clinic"? Is the phone number one digit off? Are the old and new addresses mixed up? When information conflicts, AI would rather recommend a competitor whose information is clean.
Switch two: authoritative source coverage — does your information appear in channels AI trusts?
AI weighs sources in tiers: official channels, industry media and decision-oriented Q&A communities carry far more weight than scattered free posts. Information that sits only in corners nobody looks at might as well not have been published.
Switch three: citable content — can AI lift what you write straight into an answer?
A paragraph that explains one thing clearly, with the conclusion first, data and a source: this is the kind of content AI likes to cite. Conversely, an article full of empty words gives AI nothing useful to extract.
You can check this right now. Open Doubao and, as a patient would, search "[your city] + which clinic is good for dental implants". See whether you appear in the results and whether the information is correct. That is how your clinic really looks to AI.
Do not rush in: check three conditions first
AI search optimisation is not something every clinic should start immediately. First check three conditions.
- A clear service radius. Local businesses serving anywhere from a few kilometres around to the whole city; dental clinics meet this naturally.
- Target patients who ask AI. For treatments with "heavy decisions and lots of price comparison", such as implants, orthodontics and paediatric dentistry, the share of patients asking AI is rising quickly.
- Content that can be built up. Treatment descriptions, dentist credentials, cases and FAQs: the clinic's everyday material is enough.
If you meet two or more, it is worth planning seriously. If even your platform store information is not yet in order, get the platforms right before moving on to AI; the two battlefields come in sequence.
What AI search optimisation actually involves: a four-step loop
Taking Sanqi Internet's GEO (generative engine optimisation) method as an example, the logic is straightforward.
- Calibrate "how AI sees you" first. Check the brand's basic information item by item (50+ structured fields) and make the name, address, phone number, dentists, treatments and prices consistent. Consistent information is the foundation.
- Place the information in channels AI trusts. Deploy according to a source matrix, covering official channels, industry media and decision-oriented Q&A in layers, so AI has evidence and is confident enough to cite it.
- Keep producing citable content. Write articles and Q&As around the questions patients actually ask, with one answer per question, complete in meaning and ready to be cited directly.
- Review the data weekly and keep calibrating. Are the core terms listed? Are the descriptions right? Is there negative information? Feedback every Monday, and correct whatever is wrong.
The result of this work is that AI "has evidence and is confident enough to cite you" when answering dental questions. It is not about paying for a position but about building solid information assets.
Frequently asked questions
How long does it take for a clinic to see results from AI search optimisation?
It depends on the information base. For clinics with consistent information and complete sources, changes in core-term listings can usually be seen within 1–3 months. Clinics with messy information need calibration first, so it takes longer. The key is ongoing calibration; it does not end with one deployment.
How is AI search optimisation different from traditional SEO?
Traditional SEO optimises rankings; AI search optimisation looks at whether you appear in the AI's answer. The former competes on keyword positions; the latter competes on information assets and source credibility. When a user asks "which dental clinic nearby is good?", AI generates an answer directly and recommends clinics, so the logic is completely different.
How can you tell whether a GEO agency is trustworthy?
Look at four things. First, whether it has real cases (same city, similar size, with time periods and before-and-after data). Second, whether its method can be verified (how information calibration is done, how the source matrix is built). Third, whether its data is transparent (weekly feedback on listings). Fourth, whether the contract sets limits (no guarantee of listing, but a refund clause if listing is not achieved). At Sanqi Internet, for example, the GEO service comes with a dedicated five-person team, feedback every Monday and a refund under the agreement if listing is not achieved within the agreed period. All of this can be clarified before working together.
Platform operations or AI search optimisation: which first?
Platforms are today's revenue; AI is tomorrow's entry point. If the budget allows, run both in parallel. If it is limited, get the platform store's basic information in order first, then add AI search. The two battlefields come in sequence, but do not defend only one.
Our clinic's information is quite messy. Can we still do this?
Yes. Messy information is exactly why you should start. The first step of Sanqi Internet's GEO service is calibrating the brand's basic information, checking 50+ fields item by item, to sort out "how AI sees you" before deploying content. Rolling out content while information is inconsistent only reinforces the wrong information.
Is AI search optimisation a long-term investment or a one-off job?
It is a long-term asset. Platform traffic is rented (stop paying for promotion and it falls away), while AI information assets accumulate: content, sources and reputation keep building up and become more valuable over time. That is why it is worth doing properly rather than treating it as a one-off project.