To improve your website’s chances of appearing in AI-generated search answers, start with sound SEO: make pages crawlable and eligible for Search, publish genuinely useful original content, and organize it clearly. GEO—generative engine optimization—is a newer label for work focused on visibility or citations in generated answers, not a proven replacement for SEO. For Google Search specifically, Google says optimization for generative features is still SEO.
What GEO means—and how it relates to SEO
Generative engine optimization (GEO) describes efforts to improve a website’s visibility, use, or citation in generative engine responses. The term was formalized in a 2024 paper by Pranjal Aggarwal and co-authors, which introduced a framework and the GEO-bench evaluation. The paper reported visibility improvements of up to 40% in its evaluation, with results varying by domain. That is an experimental maximum, not an expected average, a guaranteed commercial outcome, or proof of what current search products will deliver. Read the paper.
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SEO and GEO have overlapping aims but are not identical labels. SEO traditionally focuses on visibility in ranked search results; GEO emphasizes whether a site’s material is used or cited inside a generated answer. That distinction is useful as a working model, but platform behavior and measurement differ. Google’s official guidance is clearest for Google Search: “From Google’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.” Google’s guide for website owners was updated July 10, 2026.
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| Working comparison | SEO | GEO |
|---|---|---|
| Primary objective | Visibility in ranked search results | Presence, use, or citation within generated responses |
| Common measurement | Rankings, impressions, clicks, and visits | Platform-specific impressions, mentions, or citations |
| What the site owner controls | Content and technical eligibility, among other site factors | The same site factors, plus exposure to a proprietary retrieval and answer process |
| Evidence base | Established Search practices | A newer, heterogeneous field with differing terminology, metrics, and evidence standards |
This is not a claim that every AI search product retrieves or ranks pages the same way. The available current official guidance here establishes Google’s case best; platform-specific advice for other products needs their own documentation.
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How to improve your chances in Google’s AI search features
Google describes AI Overviews and AI Mode as building on its core Search ranking and quality systems. Its guide explains that generative features can use retrieval-augmented generation, or grounding, to retrieve relevant pages from the Search index; query fan-out can issue related searches to address parts of a user’s question. This describes Google’s system, not a universal architecture for AI search.
1. Keep pages eligible for Google Search
A page must be indexed and eligible to appear with a snippet in Google Search to be eligible for its generative features. Check that important pages are publicly accessible to Googlebot, that technical issues do not block crawling, and that the content can be indexed. Eligibility does not guarantee crawling, indexation, or display. Google puts it plainly: “Just because a page meets all requirements, best practices, and complies with the policies, doesn’t mean that Google will crawl, index, or serve its content.”
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2. Create work that adds something
Prioritize content that answers a real reader need with original insight, expertise, or firsthand experience. Google advises against pages that merely repackage what is already available. Do not imply that you tested a product, interviewed someone, or observed a result unless you actually did. A useful page can synthesize information, but it should make its own value clear rather than restating common material.
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3. Make pages clear for people and machines
Use a logical page structure, descriptive headings, and clear language. Put related information together and make important answers easy to locate without fragmenting every page into tiny pieces. Semantic HTML is encouraged because it supports accessibility and can make content easier to parse, but Google does not require perfect semantic code. Add high-quality images or video where they genuinely help explain the subject.
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4. Use AI carefully and avoid scaled filler
AI can help with research or structuring, but the finished pages still need to meet Google Search Essentials and spam policies. Do not mass-publish near-duplicate pages targeting tiny query variations in an attempt to win generated answers: Google says producing many pages without user value may violate its scaled content abuse policy. Google’s guidance on generative AI content was updated December 10, 2025.
5. Keep ordinary technical SEO in the workflow
Continue maintaining accessible navigation, sensible internal linking, useful page titles, and sound technical implementation. Structured data can support general SEO and eligibility for certain rich results, but Google does not present it as a special GEO requirement. Its guidance also says there is no Google-specific requirement to create an llms.txt file, add special AI markup, rewrite copy in an AI-only style, or split all content into micro-chunks. Do not trade proven usability and accessibility work for an unverified shortcut.
How to measure Google AI Search visibility
Google Search Console’s generative AI performance report covers impressions from AI Overviews and AI Mode. It offers page, country, date, and device views, with report dates in Pacific Time. The chart aggregates by property unless a URL filter is applied; newest data can be preliminary, and the usual Search performance table limits, including 1,000 rows, apply. Google’s Search Console report documentation describes its scope and dimensions.
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Use those impressions as a Google-specific exposure measure. They are not a complete accounting of AI-search traffic, a cross-engine citation-share metric, or proof that a particular content change caused a lift. For a useful comparison, record a baseline, note exactly which pages or changes you are evaluating, and compare the same platform and dimensions over a consistent period. If you use third-party visibility software, treat it as a workflow aid: Google says external tools do not have access to its internal ranking or AI systems.
What to do for AI search products beyond Google
Apply the durable principles—publish useful, accessible material and make your site technically sound—but treat product-specific tactics as hypotheses until supported by that product’s current first-party documentation or careful measurement. GEO terminology and metrics remain heterogeneous, as discussed in the July 15, 2026 critical survey, which is a preprint rather than platform policy. Read the survey. The sources available for this article do not establish current first-party GEO rules or comparable measurement methods for Bing, ChatGPT Search, or Perplexity, so claims about how to optimize specifically for those services should be verified against their own documentation.
Quick Recap
A practical starting checklist
- Confirm important pages are crawlable, indexable, and eligible to appear with a snippet in Google Search.
- Improve pages with original, reader-focused information rather than thin variations of the same answer.
- Use clear organization and accessible page structure; add media only when it helps answer the question.
- Keep structured data and other technical work tied to their general Search uses, not promises of AI citation.
- Record a Search Console baseline and evaluate changes using consistent page, date, country, or device views.
- For non-Google products, verify current official guidance before applying platform-specific tactics.
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