What Does Google Actually Say About AI Search Optimization?
Hi, I'm Saar - a software engineer, SEO specialist, and lecturer who loves building tools and teaching tech.
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- AI search uses the same index as regular Search. Google AI Overviews and AI Mode are powered by retrieval-augmented generation (RAG) on Google's existing index — there is no separate AI ranking system to optimise for.
- AEO and GEO are still SEO. Google stated explicitly: "optimizing for generative AI search is optimizing for the search experience, and thus still SEO."
- Four things that actually work: non-commodity content with a unique point of view, crawlable and indexable pages, images and video, and strong E-E-A-T signals.
- Five things to stop doing: creating llms.txt files, chunking content for AI, rewriting for AI-specific phrasing, seeking inauthentic mentions, and over-focusing on structured data specifically for AI.
Why This Article Is Different From Every Other AI SEO Guide
Most AI search optimisation advice comes from third-party research, tool vendors, or reverse-engineering AI responses. In May 2026, Google published its first official, detailed guide to optimising for AI search features — specifically AI Overviews and AI Mode. This article is a close reading of what Google actually said, not what the SEO industry speculates.
The reason this matters: Google's guidance contradicts several widely-sold "AI SEO" tactics directly. Understanding the difference between what Google confirmed and what the industry invented could save you significant wasted effort.
How Google's AI Search Actually Works
Before optimising anything, it helps to understand the mechanism. Google's AI features rely on two core techniques:
Retrieval-Augmented Generation (RAG)
RAG — also called "grounding" in Google's documentation — is the technique that drives AI Overviews and AI Mode. When a user submits a query, Google's AI does not generate an answer from training data alone. Instead, it retrieves relevant, up-to-date pages from Google's core Search index, reviews specific information from those pages, and generates a response grounded in that retrieved content. Clickable source links in AI answers point back to those retrieved pages.
The implication is direct: if your page is not in Google's Search index, it cannot appear in an AI Overview or AI Mode response. There is no alternative path in.
Query Fan-Out
AI Mode uses a technique called query fan-out: when a user asks a question, the system generates multiple concurrent, related sub-queries behind the scenes to gather broader context. For example, a query like "how to fix a lawn full of weeds" might fan out into "best herbicides for lawns," "remove weeds without chemicals," and "how to prevent weeds in lawn." Pages that answer related questions in your niche can be surfaced even without an exact match to the original query.
This means comprehensive, topically authoritative content can earn AI visibility for queries it was never specifically written for.
Is AEO or GEO a Separate Discipline From SEO?
No — and Google said so directly in their guide:
"Optimizing for generative AI search is optimizing for the search experience, and thus still SEO."
AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are terms the industry uses to describe work focused on visibility in AI search experiences. Google acknowledged the terms but was clear: from their perspective, these are just SEO. The signals that determine traditional search rankings — quality, authority, E-E-A-T, technical health — are the same signals that determine AI Overview inclusion.
This has a practical consequence: strategies that diverge from foundational SEO in the name of "AI optimization" are not supported by how Google's systems actually work.
What Google Says Actually Works
1. Create Non-Commodity Content With a Unique Point of View
Google drew an explicit distinction between commodity content and non-commodity content. Commodity content — for example, "7 Tips for First-Time Homebuyers" — is based on common knowledge that anyone could produce and adds little unique insight. Non-commodity content — for example, "Why We Waived the Inspection and Saved Money: A Look Inside the Sewer Line" — provides expert or first-hand takes that go beyond what is already widely available.
Google stated this will likely influence AI visibility more than any other factor over the long run. Practically: write from genuine experience or expertise. Do not simply restate what others have already published, and do not produce content that a generative AI model could easily generate from public information.
2. Keep Your Technical SEO Foundation Solid
To be eligible to appear in AI features at all, a page must be indexed and eligible to appear in Google Search with a snippet. All existing technical SEO best practices apply directly:
- Crawlability: Googlebot must be able to reach and crawl your pages. For large or frequently-updated sites, Google recommends reviewing crawl budget optimisation.
- JavaScript: Follow standard JavaScript SEO best practices. Google can process JavaScript content as long as it is not blocked, but JS-heavy sites add complexity.
- Page experience: Pages should display correctly across all devices, load quickly, and make it easy for users to distinguish the main content from other elements.
- Duplicate content: Duplicate pages waste crawl resources and create a poor user experience. Reducing duplication remains worthwhile.
3. Add High-Quality Images and Video
Google explicitly noted that AI search features can surface relevant images and video — meaning these create additional opportunities for your site to appear beyond web page links. If your content would benefit from visual support, adding high-quality, relevant images and video is a direct lever for AI visibility, not just traditional SEO. Following Google's image SEO best practices and video SEO documentation covers both.
4. Optimise Local and Ecommerce Details
AI responses can include product listings and local business information. For businesses with physical locations or product catalogues, Google Business Profile and Merchant Center feeds are the relevant signals. Google noted their Business Agent — a conversational experience on Search — as an emerging channel for customer interaction. These are the same tools used for traditional Search visibility; no separate AI-specific setup exists.
What Google Says to Stop Doing
This section is the most practically valuable part of Google's guide. It directly addresses popular "AI SEO" tactics by name and confirms they do not work. Each of the following is an explicit item from Google's official myth-busting section:
Myth 1: Create llms.txt or Other AI-Specific Files
What the industry says: Adding an llms.txt file to your site signals to AI systems what content to include and how to understand it.
What Google says: "You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search." Google may discover and crawl many file types on a website — this does not mean any file receives special treatment in AI features.
The practical takeaway: Do not invest time in llms.txt. It has no confirmed effect on Google AI search visibility.
Myth 2: "Chunk" Your Content for AI
What the industry says: Breaking content into small, self-contained pieces helps AI systems parse and extract information more reliably.
What Google says: "There's no requirement to break your content into tiny pieces for AI to better understand it. Google systems are able to understand the nuance of multiple topics on a page and show the relevant piece to users." Page length should be determined by what your audience needs — not by AI parsing assumptions.
The practical takeaway: Write for your readers. Make sections clear and logically organised because that helps humans, not because you are pre-chunking for AI.
Myth 3: Rewrite Content Specifically for AI Phrasing
What the industry says: Use specific phrasing patterns, long-tail keyword variations, and AI-friendly sentence structures so that AI systems can match your content to more queries.
What Google says: "AI systems can understand synonyms and general meanings of what someone is seeking, in order to connect them with content that might not use the same precise words. This means you don't have to worry that you don't have enough long-tail keywords or haven't captured every variation of how someone might seek content like yours."
The practical takeaway: Write naturally for your audience. Do not create separate pages targeting every query variation — doing so primarily to manipulate rankings violates Google's scaled content abuse policy.
Myth 4: Seek Mentions Across the Web to Boost AI Visibility
What the industry says: Getting your brand mentioned on blogs, forums, and directories trains AI systems to associate your domain with your topic area, boosting citation rates.
What Google says: AI features can show what is being said about products and services across the web — but "seeking inauthentic mentions across the web isn't as helpful as it might seem. Our core ranking systems focus on high-quality content while other systems block spam; our generative AI features depend on both."
The practical takeaway: Earn mentions genuinely through quality content and real community participation. Inauthentic placements are caught by spam systems and do not improve AI visibility.
Myth 5: Over-Focus on Structured Data Specifically for AI
What the industry says: Adding specific schema.org markup types signals your content to AI systems in a way that boosts AI citation rates.
What Google says: "Structured data isn't required for generative AI search, and there's no special schema.org markup you need to add." Structured data remains worthwhile as part of a general SEO strategy because it helps with eligibility for rich results — but it has no confirmed special effect on AI Overview inclusion specifically.
The practical takeaway: Keep using structured data for rich results and general SEO. Do not add schema specifically because you believe it unlocks AI features — it does not.
How This Changes How You Should Think About AI Visibility
Google's guidance reshapes the mental model for AI search in a useful way. Instead of asking "how do I optimise for AI search separately?", the correct question is "how well does my site perform in Google Search — and is my content genuinely better than what competitors offer?"
Measuring your AI visibility is ultimately measuring whether your SEO and content quality are strong enough for Google's systems to choose you as a cited source. Tools like Greadme's AI Visibility Analyzer show you whether AI models are currently mentioning your domain when users ask questions in your niche — giving you a measurable baseline. When your appearance rate is low, the fix is not an AI-specific hack; it is the same SEO work Google has always rewarded: better content, stronger authority, and clean technical health.
For more on the specific tactics that improve content quality for AI citation — statistics with attribution, direct-answer paragraphs, authoritative quotations — see how ChatGPT and Google AI citations work and the SEO vs AEO complete guide.
FAQ
Does Google's guidance apply to ChatGPT and Perplexity too?
Google's guide covers Google's own AI features — AI Overviews and AI Mode. ChatGPT Search and Perplexity use different retrieval backends (Bing index and own crawlers respectively) and have their own signal preferences. The foundational principle — that quality, crawlable, authoritative content performs best — applies across all systems, but the myth-busting section is specific to how Google's products work.
If AI search is just SEO, why does my site rank on Google but not appear in AI Overviews?
AI Overviews retrieve from the Search index but do not surface every indexed page. They favour pages that are already ranking well for the query, have strong E-E-A-T signals, and contain clearly extractable passages that answer the specific question. Ranking in the top 10 organic results is the strongest predictor of AI Overview inclusion (SE Ranking, 2024). If you rank but still do not appear, focus on content clarity and extractable direct-answer paragraphs.
Should I stop using structured data if it does not help AI specifically?
No. Structured data remains worthwhile for rich results eligibility — FAQPage, Article, Product, and HowTo schema all improve how your pages appear in traditional Search and can increase click-through rates. Google's point was narrower: there is no special schema type that unlocks AI features. Keep using structured data for its proven SEO benefits.
What is the difference between AI Overviews and AI Mode?
AI Overviews appear as a generated summary at the top of standard Google Search results for eligible queries. AI Mode is a fully AI-driven search experience where the entire result is a conversational AI response with source links, powered by query fan-out. Both rely on the same Search index and the same core ranking systems.
Does Google's guide change the value of AEO or GEO as a practice?
It clarifies rather than eliminates it. AEO and GEO as a set of content tactics — writing direct-answer paragraphs, adding sourced statistics, structuring FAQ blocks, allowing AI crawlers — remain valid because they genuinely improve content quality. What Google pushed back on is the idea that AEO/GEO requires a separate strategy from SEO. The tactics are valid; the framing of them as a different discipline is not.
What are agentic experiences and should I prepare for them?
AI agents are autonomous systems that perform tasks on behalf of users — booking, comparing products, gathering information. Browser agents access websites directly by analysing visual renderings, DOM structure, and the accessibility tree. Google noted that preparing for agents — such as good accessibility, clean DOM structure, and fast load times — is worth considering if relevant to your business. Protocols like Universal Commerce Protocol (UCP) are emerging in this space. This is forward-looking, not urgent for most sites today.
Conclusion
Google's official guidance on AI search optimizationdelivers two things most AI SEO content does not: a clear technical explanation of how AI features actually work, and an explicit list of popular tactics confirmed not to work. The mechanism is RAG on the existing Search index. The path in is the same as it has always been — quality content, technical health, and genuine authority. The things to stop doing include llms.txt files, content chunking for AI, AI-specific phrasing rewrites, and inauthentic mention campaigns. If you apply foundational SEO principles and create content that humans genuinely find valuable and original, you are already optimising correctly for Google's AI search features.