Gemini’s grounding step reuses Google’s index, so the technical work that makes you eligible in Search is the same work that makes you eligible there. No other major engine has that direct a relationship with something you already measure.
Which makes it the easiest engine to improve on and the most misleading one to generalise from, because the rest run their own retrieval over corpora your Search performance says nothing about.
Grounding is the step where a model stops relying on what it memorised and goes to look something up. For Gemini, the place it looks is Google’s index, and that single fact explains most of what is distinctive about how it behaves toward brands.
What does grounding mean here?
The same architecture as every other live-search engine, with a different corpus behind it.
The pattern is retrieval-augmented generation, set out in Lewis et al.: pair what the model holds in its weights with a lookup over an external corpus at query time, because a model’s ability to access what it memorised is unreliable. What varies between engines is which corpus, assembled by which crawler.
Gemini and Google’s other AI surfaces draw on the Search index. Your existing indexing status is the eligibility question.
OpenAI and Perplexity each document dedicated crawlers. Your Google performance is not an input to either.
What does that mean for eligibility?
It means there is no separate AI project, and Google says so directly.
For its AI surfaces, Google states there are “no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary”, and that to qualify as a supporting link “a page must be indexed and eligible to be shown in Google Search with a snippet”. The company explicitly tells site owners not to build AI-specific text files or custom markup.
So the entry ticket is ordinary technical SEO: crawlable, indexed, snippet-eligible. If you have that, you are eligible. If you do not, nothing else on this page helps.
Not indexed is not eligible, whatever else is true about the page.
An old blanket nosnippet, per Google’s snippet documentation, removes exactly the eligibility this depends on.
No separate file, no special markup, no second technical project. Building one is wasted effort here.
Does ranking well guarantee being named?
No, and this is where the relationship stops being simple.
Eligibility and inclusion are different steps. Being indexed and snippet-eligible makes you a candidate; whether a generated answer names your company is decided after that, from a retrieved set assembled for the question rather than from your position on one query. So a page can rank first and contribute nothing to a recommendation list, which is the single most disorienting result in this discipline.
The useful framing is that your Search work buys you a ticket rather than a seat. It is necessary on this engine and it is not sufficient anywhere.
Why is Gemini a bad proxy for the others?
Because the thing that makes it convenient is exactly the thing the other engines do not share.
If you measure only Gemini, you are measuring a surface whose corpus is the one you have been optimising for years. It will tend to flatter a team with good SEO and it will move when your SEO moves, which feels like signal and is partly just your existing work being reflected back.
Strong on Gemini, weak elsewhere
Your own domain is in good shape and the wider corpus is thin. Classic profile for a company with excellent SEO and little independent coverage.
Evidence gap
Weak on Gemini, strong elsewhere
Unusual, and it points at a Google-specific technical problem: indexing, snippet eligibility, or a page that cannot be crawled.
Cheap to fix
Weak everywhere
Entity or access, not a per-engine issue. Diagnose that before touching anything Google-specific.
Start upstream
What does grounding not fix?
Two things, and both matter for how much weight to put on a grounded answer about your company.
Grounding raises the odds that a statement traces to a document. It does not guarantee it. A generated answer can still contain a claim no retrieved source supports, which is why a stale price or a removed feature can appear inside an otherwise well-sourced response. “It cited three sources” is not the same as “everything it said came from them”.
And grounding cannot repair a corpus that is wrong about you. If every document the retriever finds repeats an outdated description, the retrieval worked perfectly and the answer is still wrong. That failure sits upstream of the architecture, on somebody else’s page, and no amount of Google-side work reaches it.
Currency. A fetched document beats a memory from before the training cutoff.
A corpus that agrees on something false. Retrieval faithfully surfaces the wrong consensus.
Is Gemini the same as AI Overviews and AI Mode?
No, and treating Google as one number throws away the most useful signal the family produces.
All three draw on the same index and they are three different products that can answer the same question differently on the same day. AI Mode in particular “uses a ‘query fan-out’ technique, issuing multiple related searches concurrently across subtopics”, which means it can name brands that rank nowhere for the query as originally asked.
Gemini is the conversational surface, and its retrieval depth varies with how a question is put. Track all three as separate rows, because a disagreement between them is a diagnosis rather than noise.
What should you actually do?
Almost nothing Gemini-specific, which is the honest conclusion and an unpopular one in this category.
Keep the site crawlable and indexed. Check you have not restricted snippets. Write sections that stand alone, since retrieval scores passages rather than whole documents. Then spend the rest of your effort on the layer that decides inclusion rather than eligibility, which is what independent sources say about you, and which is the same work that helps on every other engine.
What is the one Gemini-specific check worth doing?
Confirming that your Search eligibility is genuinely intact, because that is the whole gate and it fails silently.
Three things break it, and none of them look like an AI problem from the inside. A page that is not indexed cannot be a candidate. A snippet restriction removes the eligibility the surface depends on. And a robots rule can prevent crawling, though it is worth remembering that robots.txt governs crawling rather than appearing: Google states it “is not a mechanism for keeping a web page out of Google”, since a disallowed page can still be indexed when other sites link to it.
Check those three before running a single prompt. An audit of a site that is not snippet-eligible measures your configuration rather than your visibility, and you will spend a quarter fixing the wrong layer.
How the engines split into families is in the engine guide, why ranking and recommendation come apart is in ranking first and appearing nowhere, and the two other Google surfaces are covered in AI Overviews vs AI Mode.