With AI answering everything, does a website still make sense?
- Redazione
- 13 hours ago
- 6 min read
Something has been happening in recent months that many companies are aware of, but are struggling to understand: people search for information, get an answer… and no longer click on any site .
It happens on Google, it happens in reply boxes, it happens more and more often directly within tools like ChatGPT, Gemini, or Perplexity.
From here comes a term that until recently did not exist: AI visibility .
The problem is that almost everyone talks about it assuming you already know what it means .
So let's start from the basics, without shortcuts.
Summary
What is AI visibility really?
Simply put, AI visibility is the ability of content to influence a response generated by an AI-based engine, even when that AI isn't sending direct traffic to the site that produced that content.
It's important to state this right away: AI visibility doesn't equate to Google rankings , nor does it even equate to "being cited." Many articles start from an implicit assumption:
To be visible in AI you must become a reference, an authority, a recognized source.
This assumption is convenient.
And it's also wrong for most SMBs . In B2B, it's often completely unrealistic.
So let's pause for a moment and ask a more honest question: if no one ever sues me, does it still make sense to work on visibility in AI engines?
The answer is yes , but for different reasons than the gurus say .
From search engine to answer engine
For years we've thought of search like this: the user searches, Google displays results, the user clicks, the site "wins."
Artificial intelligence hasn't broken this pattern. It's made it explicit .
Today, more and more often, the process is: the user asks a question, receives an answer, and only then , if necessary, does he or she delve deeper. Clicking is no longer a mandatory step. It's an option.
This doesn't mean that websites are no longer useful. It just means that they serve a different purpose at a different point in the decision-making process .
Why “becoming an authority” is useless advice for many companies
It is worth being very clear here.
When you read that to be visible in AI you have to “become authoritative,” the real question is: authoritative for whom?
Most SMEs:
has few customers
works in narrow niches
it is not mentioned by the media
it will never be a “source” in the editorial sense
In B2B the situation is even more evident:
few players
direct relationships
complex decisions
content that is not very “quotable”
Telling these companies to "become a point of reference" is like telling a carpentry shop: become a trade magazine...
It's not a strategy. It's an elegant way of not responding.
So what is AI visibility really for an SMB?
For an SME, AI visibility doesn't mean being named . It means being consistent with how a response is constructed .
LLMs don't choose the most famous. They choose what:
it's clear
it is unambiguous
it is internally consistent
responds to a specific problem
In other words: you don't have to be a recognized source, you have to be an understandable source.
And that's a huge difference.
Zero clicks, zero visits… zero value?
When it comes to click-free responses, the risk is panic: if no visits come, then all this is for naught.
It's an old reading.
In many sectors – especially consulting, services, B2B – the AI response:
does not close the decision
orient
narrows the field
create a mental frame
When a user arrives on the site, they aren't neutral . They're checking it out, not exploring.
The website is no longer a place of discovery. It's a place of validation and trust .
The website is still central (but not for the reasons it was before)
No, the site isn't dead. But yes, the site needs to change its function. For at least the next five years, the site will remain central because:
AI does not take responsibility
AI doesn't sign contracts
AI doesn't know your specific context
AI not answering the phone (+ or -)
The site serves to:
give depth
reduce perceived risk
show consistency
make a previously made choice credible
It's no longer a megaphone. It's the landing point of trust.
What the study really says (with data, not slogans)
The study published by Wix Studio ( AI Search Lab – On-page factors for AI visibility ) is interesting because it does not talk about fame, but about readability .
Here is a summary of the main factors that emerged, reinterpreted from an SME perspective:
On-page factor | Impact on AI visibility | Why it matters |
Clear structure (H1–H2–H3) | High | AI understands content without interpretations |
Explicit answers | Very high | Reusable responses are favored |
Semantic coherence | High | Reduces ambiguity |
Content Focus | Very high | Generic texts are ignored |
Data explained | Most High | Contextualized numbers are more reliable |
Source: Wix Studio – AI Search Lab https://www.wix.com/studio/ai-search-lab/research/on-page-factors-for-ai-visibility
Translated: LLMs work best with clean content , not “authoritative” content.
SEA and transactional searches: fewer clicks, but more value
Another common mistake to avoid here is thinking that everything will become zero-click.
Transactional searches aren't zero-click , and they're unlikely to be anytime soon. AI doesn't buy, doesn't pay, and doesn't assume responsibility.
What's happening is different:
fewer clicks overall
more conscious clicks
higher average value per visit
This applies to both transactional SEO and SEA ads .
Campaigns aren't disappearing. They're working further down the funnel, reaching already-oriented users.
And this is exactly why the website and its contents remain fundamental.
Original content: why it matters more than quotes (real case study)
Here we come to a point that is often overlooked.
Many talk about "citations" as a goal. But in the reality of SMEs, citations are often a consequence , not a lever.
For example, on this Hangler blog there is an article on “ how much does a website cost ” that works exactly in this direction: not chasing the citation, but producing content that is difficult to replicate .
It's a content:
based on real data collected on concrete projects
enriched by contextualized market numbers
written from direct experience, not from reworkings
not copied or rewritten from other sources
Result:
the article is positioned on the first page of Google for several relevant keywords
at the same time it is considered relevant by AI engines , as AI search tools show
This point is crucial: visibility in AI engines is not an alternative to visibility on Google.
When content provides original and verifiable information , it tends to work:
in traditional search engines
in LLM-based response systems
And this is exactly where SMEs can play a real game, without chasing unattainable models.
The quote is a side effect, not the goal
It's worth saying clearly:
no, not all companies will be cited
no, you don't need to become famous
no, there is no point in chasing authority as an abstract concept
You need:
bring your own data
explain real decisions
give context
say even non-obvious things
If the AI uses that content, great. If it doesn't mention the name, the result won't change : the user will be more prepared, more oriented, more aware.
Conclusion
The real mistake today isn't not being cited by AI. It's continuing to produce content that anyone could write.
AI visibility does not reward:
the fame
the brand
the quantity
Reward:
clarity
consistency
original data
real experience
And this is exactly the type of content that many SMEs can afford to produce, if they stop chasing gurus and start sharing what they really know without fear of revealing information that could help their competitors (so old-fashioned...!).
FAQ
What is AI visibility?
It is the ability of content to contribute to responses generated by AI-based engines, even without generating direct traffic.
Is it necessary to be cited to appear on LLMs?
No. For SMEs, it's important to be understandable and unambiguous.
What are LLMs (Large Language Models)?
Large Language Models (LLMs) are artificial intelligence models trained to understand and generate natural language text .
In practice, these are the systems behind tools like ChatGPT, Gemini, or Claude: they don't "search" for information like a traditional search engine, but build answers by combining what they've learned from large amounts of text.
The key difference compared to classic search engines is this:
Google shows a list of pages
an LLM provides a concise answer
To do this, LLMs do not choose the “most famous” contents, but those that are:
clear
consistent
not very ambiguous
useful for answering a specific question
This is why today well-written content based on real data can influence an AI response even without being the most visited or most cited site in the industry .
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