Google does not publish a separate “AI Overview optimization” trick. Its current guidance says the foundations of SEO still apply: a page must be crawlable, indexed, eligible to appear with a snippet and genuinely useful. AI Overviews and AI Mode may use multiple searches to answer a complex question, so clear topic coverage and distinctive evidence matter—but special AI schema, forced content chunks and an llms.txt file are not required for Google Search.

One terminology note: people often call this “Gemini SEO” because Gemini models power Google experiences. This guide addresses visibility in Google Search's AI Overviews and AI Mode. Google has not documented a special markup or submission route that guarantees a recommendation inside the standalone Gemini app.

Key takeaways

  • Start with normal indexation, snippet eligibility and page experience.
  • Googlebot—not Google-Extended—controls eligibility for AI features in Google Search.
  • Cover the main question and useful supporting questions; do not create doorway pages for every prompt variation.
  • Add first-hand experience, original analysis and evidence that generic summaries lack.
  • Keep important information in text and support it with useful images or video.
  • Structured data should match visible content; there is no special AI Overview schema.
  • Google says llms.txt is not needed for its Search AI features.
  • Measure both AI-search visibility and the conversions generated by the resulting visits.

Table of contents

How Google AI search discovers supporting pages

Google describes AI Overviews and AI Mode as using its core Search systems plus generative AI. For complex questions, the systems may use a “query fan-out” technique: they issue multiple related searches across subtopics and data sources, then synthesize a response with supporting links.

Imagine the query:

What is the best way for a small SaaS team to automate an English and German blog without sacrificing quality?

Useful supporting searches might concern multilingual SEO, CMS integrations, editorial review, automated internal linking, cost and publishing frequency. A shallow page that repeats “AI SEO automation” twenty times does not provide those answers. A connected set of pages with specific facts can.

Query fan-out does not mean you should generate a separate page for every conceivable wording. Google explicitly warns against scaled, low-value content. Organize the subject around real user decisions and make every indexable page meaningfully different.

1. Confirm basic Search eligibility

Google says a page must be indexed and eligible to appear in Search with a snippet to be considered as a supporting link in its AI features. Begin with the boring but essential checks:

  • Googlebot is allowed to crawl the page and its important resources;
  • the URL returns 200 and does not lead through broken or irrelevant redirects;
  • the page is not blocked by a noindex directive;
  • the canonical points to the preferred version;
  • the main content is rendered and understandable;
  • internal links and the XML sitemap support discovery;
  • the page complies with Search spam policies;
  • snippet controls do not unintentionally prevent useful previews.

Use Google Search Console for real indexation status and Bora's SEO checker for an additional on-page pass. Validate the sitemap with the sitemap checker and test directives with the robots.txt tester.

If a page is not eligible for normal Search, inventing an “AI keyword” will not repair it.

2. Understand Googlebot versus Google-Extended

These controls are frequently confused.

  • Googlebot governs crawling for Google Search, including eligibility for AI Overviews and AI Mode.
  • Google-Extended is a separate control for certain uses in Gemini models and other generative AI systems. Google states that it does not affect inclusion or ranking in Google Search.

Blocking Google-Extended is therefore not a method for opting out of AI Overviews. Likewise, allowing Google-Extended does not guarantee a citation in Search. Treat each control according to its documented purpose and your organization's policy.

3. Give the query a complete, direct answer

The opening of a page should resolve the searcher's main uncertainty, not make them scroll through a brand story. In the first section:

  1. Answer the primary question.
  2. Define the relevant conditions.
  3. State the most important limitation.
  4. Show the reader what the page will help them do.

Then use descriptive headings for supporting questions. For example, an article about blog automation could cover quality gates, CMS differences, cadence, cost, measurement and failure recovery. These are not keyword decorations; they are parts of the decision.

The complete workflow in how to automate a blog without losing quality is a good model: one central answer with distinct implementation sections.

4. Add non-commodity value

Google's 2026 guidance emphasizes unique, non-commodity content. A rewritten summary of the pages already ranking gives the system little reason to surface your page as an additional source.

Add value through:

  • first-hand experience from operating the workflow;
  • original data with sample size, dates and methodology;
  • specific screenshots, code or configuration examples;
  • a decision table built from disclosed criteria;
  • failure modes and recovery steps;
  • expert commentary with a real identity;
  • clear limitations and cases where the advice does not apply.

For Bora, a credible article can explain the differences between WordPress, Webflow and Ghost publishing APIs because the product has to handle those differences. That is stronger than a generic list of CMS logos.

The existing engineering post on what breaks when AI publishes daily should be linked wherever a claim about automation reliability is made. First-hand proof should be part of the architecture, not buried in an isolated article.

5. Build topic depth with a hub-and-spoke structure

A useful site architecture lets a reader—and a crawler—move from the broad decision to precise implementation.

For an AI-search visibility cluster, Bora can use:

Every page should link up to the conceptual hub and sideways only where the next page resolves a genuine follow-up. This produces a navigable learning path instead of a web of forced exact-match anchors.

6. Make pages easy to interpret

Clarity helps humans first. It also reduces ambiguity when systems extract a passage.

Use:

  • one descriptive H1;
  • H2s phrased around real subquestions;
  • concise definitions near the first use of a term;
  • tables for genuine comparisons;
  • ordered steps for processes;
  • descriptive anchor text;
  • captions that explain why an image matters;
  • dates and units on changing facts;
  • source links next to consequential claims.

Avoid splitting every sentence into a tiny “AI-friendly” block. Google says there is no need to rewrite pages solely to make them easier for AI systems to retrieve. Natural, well-structured writing is enough.

7. Use images and video as evidence, not decoration

Google recommends supporting textual content with high-quality images and videos where they help the user. A stock robot image rarely adds meaning. Better assets include:

  • a labeled workflow diagram;
  • an interface screenshot showing the exact setting;
  • a chart with methodology and date;
  • a before-and-after comparison;
  • a short demonstration of a multi-step task.

Compress images, reserve their dimensions to reduce layout shift and write alt text that describes their informational purpose. Bora's broader image SEO workflow can check whether media is accompanied by useful context.

8. Use structured data accurately

There is no special AIOverview or “Gemini ranking” schema. Use supported Schema.org types when they reflect visible content:

  • Organization for the business identity;
  • SoftwareApplication for a software product with real attributes;
  • BlogPosting or Article for editorial content;
  • Person for a named author or reviewer;
  • BreadcrumbList for visible navigation hierarchy.

Do not mark up content hidden from users. Do not add star ratings that are not collected and displayed according to policy. Generate a clean starting point with Bora's schema generator, then test the final markup with Google's tools.

9. Do not overestimate llms.txt

An llms.txt file is a proposed convention that some site owners use to point language-model systems toward important content. Google states that it does not need llms.txt for AI Overviews or AI Mode and that normal Search crawling mechanisms apply.

You may still evaluate the convention for other ecosystems, but it is not a replacement for:

  • crawlable pages;
  • accurate sitemaps;
  • strong internal links;
  • canonical URLs;
  • people-first content;
  • independent authority.

Do not let a ten-minute text file distract the team from the evidence and technical quality that affect the whole site.

10. Match content to the whole decision journey

AI answers can compress discovery and comparison into one interaction. Your content system should still serve different stages:

StageUser questionBest Bora page type
LearnWhat is GEO?educational guide
DiagnoseWhy is my site absent from AI results?technical checklist/tool
CompareWhich SEO automation tool fits my CMS?neutral roundup and detailed comparison
ValidateWill automation create spam?policy and quality guide
ActHow do I start?workflow, integration and pricing page

A strong article points to the next useful step without turning every paragraph into a sales pitch. This guide can send a technical reader to the crawler article, a product evaluator to Bora's features and a ready buyer to pricing.

11. Measure Google AI-search outcomes

Google's current documentation points site owners to Search Console, including its newer generative AI reporting. Use the available reporting to study queries, pages and change over time. Then connect organic traffic to engagement and conversion data.

Track:

  • pages cited or surfaced in AI-search contexts where reporting is available;
  • query themes, not only individual keywords;
  • impressions and clicks to the supporting pages;
  • engaged sessions and assisted conversions;
  • newsletter, trial or demo actions;
  • branded search change after high-visibility coverage;
  • technical eligibility errors.

Do not celebrate an impression trend if the destination page cannot convert the right audience. The complete AI visibility measurement framework separates presence, traffic and revenue.

Common AI Overview optimization mistakes

Publishing a generic answer at scale

More URLs do not create more expertise. Consolidate overlapping drafts and add evidence.

Creating pages for every query fan-out variation

This can become doorway content. Use sections or genuinely distinct supporting pages based on user needs.

Claiming a special Gemini schema

No documented markup guarantees inclusion. Use normal structured data that matches the page.

Blocking Googlebot while allowing another AI token

Search eligibility still depends on Googlebot and Search controls.

Adding fake brand mentions

Google explicitly discourages inauthentic mentions designed for AI visibility. Earn references through useful work and real relationships.

Measuring only clicks

AI experiences may change click behavior. Track presence, citations, brand demand and conversion quality alongside traffic.

A practical publishing checklist

  • [ ] The page is indexable, canonical and snippet-eligible.
  • [ ] The answer appears early and matches the intended page type.
  • [ ] Supporting questions are covered without filler.
  • [ ] The article includes first-hand or original value.
  • [ ] Important claims have primary sources and dates.
  • [ ] Internal links connect the topic, evidence and conversion pages.
  • [ ] Images or video teach something useful.
  • [ ] Structured data matches visible content.
  • [ ] A real author or reviewer accepts responsibility.
  • [ ] Search and conversion reporting is configured.

Where Bora fits

Bora can automate the repeatable parts of this system: topic research, structured drafts, supporting images, internal links, metadata, schema, multilingual publishing and CMS delivery. Teams can use the content analyser to review a page and the product workflow to maintain coverage over time.

Human ownership remains essential for product facts, original evidence, expert review and honest comparisons. That combination—automation for consistency, people for judgment—is safer than either mass production or an unmaintainable manual process.

If you want to turn this checklist into a recurring workflow, see how Bora works or compare plans.

Sources and freshness notes

Editorial implementation notes

  • Verify Search Console feature names and availability for the target property before publishing screenshots.
  • Keep the distinction between Google Search AI features and the standalone Gemini app in the introduction.
  • Replace the author placeholder and add a real review date.
  • Use BlogPosting JSON-LD and avoid unsupported AI-specific schema claims.