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Google AI Mode: what changes for a publisher

Published 11 September 2026 · Updated 12 October 2026 · 9 min read

Google AI Mode: what changes for a publisher
Photograph: Fernando Hernandez / unsplash

The short answer: Three things change for a publisher, and Google documents each one. Your page can be retrieved against sub-queries you never wrote, because Google says AI Mode may split one question into several searches behind the scenes. Your reporting changes, because Search Console now carries a separate generative AI report that counts impressions and no clicks. And you hold a property-level switch that removes you from those surfaces, which Google says is not used as a ranking or inclusion signal elsewhere in Search.

The rest of what gets sold as AI Mode strategy is, on our reading, ordinary technical hygiene under a new label. That is a judgement from audit work, not a claim Google makes.

One scope note before the detail. Everything below is about Google. Other engines retrieve, cite and report differently, they publish their own guidance, and nothing here should be read as describing them.

The fan-out is the mechanism worth understanding

Google's AI features documentation, last updated 10 December 2025, says both AI Overviews and AI Mode may use a technique it calls query fan-out: issuing multiple related searches across subtopics and data sources to develop a response. Note the word may. Where fan-out runs, the query that surfaced your page need not be the query the user typed. Google does not publish how often it runs or what triggers it, so nobody outside Google can put a frequency on it, and we do not.

Someone asks which payroll tool handles contractors in three countries. Behind that, the system may run half a dozen narrower searches: contractor payroll compliance, multi-currency payouts, a pricing comparison, a complaints thread. Your page competes inside one of those narrow slots, not against the original sentence. A page that answers the broad question well and the narrow one vaguely is competing badly for that slot. That last sentence is an inference from the documented mechanism, not a measured result: the sub-queries are not exposed to publishers, so we cannot see which slot a page lost.

That is why, in the audits we run, the fix is more often a subheading that states a specific condition followed by two sentences that settle it, than a new article. That is a recommendation drawn from the documented mechanism, not an outcome we have counted. The same logic drives how each AI engine picks the sources it cites, and it is the reason the retrieval layer deserves more attention than the writing layer.

Queries got longer, and Google published the figures

Google published usage figures for AI Mode on 19 May 2026, one year after the United States launch. Three of them matter to anyone writing pages. The average AI Mode search is triple the length of a traditional Search query. More than one in six searches in the United States now use voice or images rather than typed text. And AI Mode queries have more than doubled every quarter since launch, which Google states without a country attached in a post otherwise about the United States.

All three are Google's own figures, dated 19 May 2026. Google publishes no sample size, no measurement window and no method for any of them, so they are a vendor's self-report about its own product. They are worth reading as direction, not as something an auditor could reproduce.

Longer queries carry conditions. Industry, team size, a constraint, a deadline. A page built around a two-word head term can keep its classic ranking and still miss the clause that decides the answer. Google has published nothing connecting query length to which pages its AI features cite, so the step from the first figure to that advice is ours, not Google's.

Your reports changed, and the gap in them is the point

On 3 June 2026 Google shipped Search Generative AI performance reports in Search Console, and on 31 August 2026 rolled them out worldwide. They cover impressions, pages, countries, devices and dates, with hourly through monthly granularity. The Search report covers AI Overviews and AI Mode together, and Discover has a separate generative AI report of its own.

Read that list again for what is absent. The Search Console help page for the report lists impressions as the metric, and pages, countries, dates and devices as the dimensions. There is no click count, no click-through rate and no query dimension in that dedicated view. You can learn that a URL appeared inside an AI surface in Germany on a phone. You cannot learn what was asked. Google has said it is considering additional metrics over time.

Clicks from these surfaces are not invisible everywhere. Search Console's methodology page says a click on an external link inside AI Mode or an AI Overview counts as a click, and that data sits in the overall performance report, where no documented filter separates it from the rest of Search. So the honest statement to a board is narrower than it sounds: appearances are countable per surface, and outcomes from a surface are not separable with what Search Console documents today. Anyone presenting an AI Mode revenue figure is modelling rather than reading a report, and the model should be shown.

Average position stopped meaning what it used to mean

This one is a genuine trap and it is documented. Search Console's methodology page states that an AI Overview occupies a single position in search results and all links in the AI Overview are assigned that same position. Position in AI Mode, the same page says, follows the same methodology as a Google Search results page. The two surfaces are not alike here, so the trap is an AI Overviews trap specifically.

Picture the consequence. Eleven sources are named in one AI Overview and all eleven record the identical position. A site pulled into AI Overviews often can watch its average position chart flatten while its underlying performance has not moved. We have seen teams rebuild pages chasing that movement. That is an impression from client work, with no count behind it.

Here is a check that takes ten minutes. Filter the performance report to a page you know appears in AI answers, compare its average position trend before and after the gen-AI reports arrived, then overlay the impressions in the generative AI view. If position went sideways while AI impressions climbed, your position chart is probably tracking surface mix as much as performance. Report impressions by surface after that, and leave position for the queries that still resolve to a classic listing. The deeper version of this split is covered in how Google AI Overviews chooses its sources.

What Google says you do not need, in writing

Google published a guide to optimising for generative AI search, last updated 10 July 2026, and most of it is a list of things to stop doing. Google Search does not use llms.txt or similar AI text files and ignores them. Structured data is not required for these features and no special schema.org markup exists for them. Chunking your pages into fragments is not required. Rewriting copy to repeat exact phrasing is unnecessary, since the systems understand synonyms and general meaning. Seeking inauthentic mentions of your brand is not as useful as it looks.

Each of those is Google's statement about Google Search, and that is the only place it applies. Other engines publish their own guidance, some of it different, and a few publish nothing at all. Do not carry this list across to them.

None of that makes structured data pointless. It earns rich results, it resolves which organisation you are, and identity is the part most sites get wrong. That is a different argument from the one the category usually makes, and it is laid out in author and publisher markup that survives scrutiny and in FAQPage and HowTo after the rich-result changes.

The control nobody reads the footnotes on

Search Console now carries a Search generative AI control, under Settings, rolled out to all properties worldwide on 31 August 2026. Exclude your property and your links and content are prevented from appearing in AI Overviews, AI Mode and the generative AI features in Discover. Google's help page says the control is not used as a ranking or inclusion signal affecting other parts of Search, and that content is excluded within one to two days of the change going live, though caching and propagation can stretch that.

Before anyone reaches for it, note what the switch costs. Removal from the surface removes you from the shortlist a buyer forms before they click anything. For a paywalled archive that may be worth it. For a product site competing on consideration, it is close to unilateral disarmament. Decide it at the property level with revenue in the room, not in a technical ticket.

Three checks to run this week

Open the generative AI view and list the ten URLs with the most AI impressions. Ask whether those are the pages you would want quoted. Expect at least one you would not have chosen, often an old comparison post. We have no count for how often that happens and are not offering one.

List the five buyer questions that matter most to revenue, add the conditions a real buyer would attach, and run each against AI Mode more than once. Record whether you were named and whether the sentence beside your name was accurate.

Then check the boring layer: does the page render its answer in the HTML, is it reachable, does the heading state the condition. The self-check walks through ten of these with no tooling involved.

Honest limits

This post establishes what Google documents about its own surfaces, and very little else. It does not establish that fan-out runs on most queries, how many sub-queries a question produces, or which one your page was retrieved against, because Google exposes none of that and we cannot measure it from outside. The three usage figures are Google's self-report about its own product with no sample size or method published, so treat them as direction rather than evidence. The advice about condition-stating subheadings is what we recommend in audits after reading the fan-out documentation, not a tested result with a control group, and we have deliberately left out any figure for how often it helps because we cannot reconstruct one. Nothing here describes ChatGPT, Perplexity, Copilot, Claude or Grok, whose retrieval and reporting differ and whose behaviour we would have to measure separately.

FAQ

Is AI Mode the same thing as AI Overviews? No. An AI Overview sits on a results page as one block among links. AI Mode is a conversational surface where follow-up turns can change which sources appear. Search Console reports them in the same generative AI bucket, which is why the numbers need care.

Do I need new markup or an llms.txt file? For Google Search, no. Google's guide, updated 10 July 2026, says Google Search does not use llms.txt and that no special structured data is needed for these features. Keep schema for rich results and entity clarity. Other engines are a separate question with separate docs.

Will blocking AI surfaces protect my traffic? The generative AI control removes you from Google's AI surfaces, and Google says it is not used as a ranking or inclusion signal elsewhere in Search. It also removes you from the answer where buyers form a shortlist. Treat it as a commercial decision with a revenue owner.

Why did my average position go flat? Links inside an AI Overview all carry the position of the Overview itself, which Search Console documents. As more of your impressions come from that surface, the position metric compresses toward one number. AI Mode is scored by the standard results-page rules, so this is an AI Overviews effect.

Sources

Every URL above was opened and checked against the sentence citing it on 12 October 2026.

Related reading

How each AI engine picks the sources it citesHow Google AI Overviews chooses its sourcesAuthor and publisher markup that survives scrutinyFAQPage and HowTo after the rich-result changesGrok and social sourcing: when posts become citations