Google Releases New Guide on Optimising for Generative AI Search

Google has just published one of the most anticipated documents in the SEO world this year: an official guide titled “Optimising your website for generative AI features on Google Search.” It’s the clearest signal yet of how Google wants website owners to think about AI Overviews, AI Mode, and the rapidly shifting search landscape.

For anyone who has been wading through conflicting advice about AEO, GEO, llms.txt files, content chunking, and a dozen other supposed AI optimisation tactics — this guide cuts through the noise. Google’s message is direct, and in many respects, reassuring. Here’s a full breakdown of everything the guide covers, what it means, and what you should do about it.

Why Google Published This Guide Now?

The timing is deliberate. AI features in Google Search — particularly AI Overviews and the newer AI Mode — have moved from limited experiments to mainstream search experiences. User behaviour is shifting, and Google acknowledges it plainly: user preferences are rapidly evolving and people are increasingly gravitating to generative AI experiences to help them find information. This transformation offers new opportunities to reach people who may be more inclined to engage with your site, spend more time with your content, or even convert by becoming a subscriber or making a purchase.

In other words, Google isn’t just acknowledging that AI search changes things — they’re framing it as an opportunity. Sites that understand how these features work can gain visibility in ways that weren’t possible before. But first, you need to understand how they actually work.

The Core Principle: AI Search Is Still SEO

The most important statement in Google’s entire guide comes right at the start. When asked whether SEO is still relevant for generative AI search, Google’s answer is unambiguous: yes! The best practices for SEO continue to be relevant because generative AI features on Google Search are rooted in core Search ranking and quality systems.

This matters enormously because a significant amount of content circulating about AI search implies that traditional SEO is being replaced by something entirely new. Google’s official position is the opposite. The same systems that determine what ranks in conventional search results are the same systems that feed AI responses.

Understanding the mechanics helps. Google’s guide explains two key techniques powering AI responses:

Retrieval-Augmented Generation (RAG) is a technique used to improve the quality, accuracy, and freshness of AI responses by relying on core Search ranking systems to retrieve relevant, up-to-date web pages from the Search index. The systems then review the specific information from those retrieved pages to generate a more reliable and helpful response, showing prominent, clickable links to relevant web pages that support the information in the response.

Query fan-out is a set of concurrent, related queries generated by the model to request more information and fetch additional relevant search results to address the user’s query. For example, if the original user’s query is “how to fix a lawn that’s full of weeds”, fan-out queries might include “best herbicides for lawns”, “remove weeds without chemicals”, and “how to prevent weeds in lawn”.

The practical takeaway from fan-out is significant: your content doesn’t need to match a user’s exact query. Google’s AI generates related sub-queries to gather information, meaning a well-written, comprehensive page on a topic can surface for searches that don’t even use your exact phrasing.

Google also addresses the terminology question directly. “AEO” stands for “answer engine optimisation” and “GEO” for “generative engine optimisation.” These are both terms you may see used to describe work specifically focused on improving visibility in AI search experiences. From Google Search’s perspective, optimising for generative AI search is optimising for the search experience, and thus still SEO.

What the Guide Says You Should Do?

Create Valuable, Non-Commodity Content

Google is emphatic that this single factor matters more than anything else for AI search visibility in the long run. The guide introduces a distinction that every content creator should internalise: the difference between commodity and non-commodity content.

Commodity content is often based on common knowledge, which could originate from anyone, and typically adds little unique insight for readers. In contrast, non-commodity content provides unique expert or experienced takes that go beyond common knowledge and the ordinary.

A first-hand review provides a unique perspective based on personal experience, whereas a summary of existing content simply restates information already available elsewhere. Create the content yourself based on what you know about the topic, and consider what in-depth experience you can bring to your content. Don’t just recycle what others on the internet have already said, or could easily be produced by a generative AI model.

This is one of the clearest statements Google has ever made about content quality. If your content could plausibly have been written by anyone — or worse, generated wholesale by AI without human expertise — it offers limited competitive advantage in AI responses. Content that draws on genuine experience, specialised knowledge, or a distinctive point of view is what gets cited.

Google also specifies how content should be structured: write content for your human audience and make sure the content is well written and easy to follow. People generally appreciate it when web pages are organised by paragraphs and sections, along with headings that provide a clear structure to navigate content.

On multimedia, the guide reinforces what’s already good SEO practice: many people appreciate finding images and videos as they search for things online. As with Google Search overall, generative AI search features can bring in relevant images and video, which means more opportunities for your website to appear beyond web page links.

There’s also an important caution about over-engineering content for AI: while it might be tempting to create separate content for every possible variation of how people might search, doing so primarily to manipulate rankings or generative AI responses in Google Search violates Google’s scaled content abuse spam policy. This is also an ineffective long-term strategy, as a high quantity of pages doesn’t make a website higher quality or more relevant to users.

Build and Maintain a Clear Technical Structure

Technical SEO isn’t optional for AI search visibility — it’s the prerequisite. The way Google Search finds and processes your pages remains the core of how AI systems access your data. Technical clarity ensures your content is ready for discovery and indexing, and all existing technical SEO best practices continue to be worthwhile.

The guide is specific about what this means in practice. On indexability: to be eligible to be shown in generative AI features on Google Search, a page must be indexed and eligible to be shown in Google Search with a snippet, fulfilling the Search technical requirements. Pages that are blocked, noindexed, or not serving snippets simply cannot appear in AI responses, regardless of content quality.

On crawlability: ensure your content is crawlable, as Google Search generative AI models use publicly accessible, crawlable content to learn patterns and provide relevant, grounded responses.

On page experience: provide a good page experience for those who arrive at your site. This includes ensuring your site displays well across all devices, reducing latency, and making it easy for people to distinguish your main content from other elements on the page.

On duplicate content: having duplicate content can be a bad user experience and search engines might waste crawling resources on URLs that you don’t even care about. If you have time, try to reduce it.

Optimise Local Business and Ecommerce Details

For local businesses and product-led sites, the guide contains specific and actionable advice. Where appropriate, generative AI responses can include product listings, product information, and information about local businesses. Using products like Merchant Center and Google Business Profiles can help your products and services be visible in both AI responses and other Google Search results.

Google also flags an emerging feature worth knowing about: depending on your business type and goals, consider other merchant experiences like Business Agent, which is a conversational experience on Google Search that helps customers chat with your brand.

The Mythbusting Section: What You Can Stop Doing

This is arguably the most practically useful part of the entire guide. Google directly dismantles a series of tactics that have been circulating as AI optimisation advice. These aren’t edge cases — they’re things many SEOs and marketers have been actively implementing.

LLMS.txt files are unnecessary. You don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search.

Content “chunking” is not required. 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. However, sometimes shorter or longer pages can work well depending on your audience and subject matter. There’s no ideal page length, and in the end, make pages for your audience, not just for generative AI search.

Rewriting content for AI systems is a waste of time. You don’t need to write in a specific way just for generative AI search. 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.

Seeking inauthentic mentions won’t work. Just like the rest of Google Search, generative AI features can show what’s being said about products and services across the web, including in blogs, videos, and forum discussions. However, seeking inauthentic “mentions” across the web isn’t as helpful as it might seem. Core ranking systems focus on high-quality content while other systems block spam; generative AI features depend on both.

Structured data is helpful but not required for AI. Structured data isn’t required for generative AI search, and there’s no special schema.org markup you need to add. However, it’s a good idea to continue using it as part of your overall SEO strategy, as it helps with being eligible for rich results on Google Search.

The Emerging Area: Agentic Experiences

One section of the guide looks ahead to something that hasn’t fully arrived yet but is worth understanding now. Google introduces the concept of AI agents interacting directly with websites to complete tasks on behalf of users.

AI agents are autonomous systems that can perform tasks on behalf of people, such as booking a reservation or comparing product specifications. These agents can take many forms; for example, browser agents may access your website to gather the data they need to complete these tasks, such as analysing visual renderings like screenshots, inspecting the DOM structure, and interpreting the accessibility tree.

Google recommends that site owners familiarise themselves with agent-friendly website best practices, and flags that protocols like Universal Commerce Protocol (UCP) are emerging that will allow Search agents to do more.

For most businesses, this doesn’t require immediate action — but it’s a signal of where things are heading. Sites with clean, accessible, well-structured HTML will be better positioned to serve both human visitors and AI agents as this technology matures.

Google’s Summary: The Key Takeaways

Google closes the guide with a concise recap of priorities. In their own words, the key takeaways are:

Apply SEO best practices to generative AI search: continue prioritising foundational SEO best practices, such as building a clear technical structure and creating unique, valuable content; these are the foundation for visibility in generative AI search experiences and Google Search overall.

Create non-commodity content that’s helpful, reliable, and people-first: focus on developing unique, expert-led content that provides value beyond common knowledge.

Prioritise effective SEO strategies over “AEO/GEO hacks”: for Google Search, you can ignore tactics like “chunking” content, creating unnecessary AI text files like llms.txt, or pursuing inauthentic mentions.

Explore agentic experiences: stay informed about emerging technologies that allow AI agents to interact with your site, such as browser agents and new protocols.

What This Means for Your SEO Strategy Right Now?

Google’s guide is clarifying in the best possible way. It confirms that the businesses investing in genuine content quality, technical soundness, and real authority are already on the right path. It also frees up resources currently being spent on unproven AI-specific tactics.

The practical priorities that flow from this guide are straightforward:

Audit your content for commodity vs. non-commodity value. Ask honestly whether each piece of content you publish brings something that couldn’t have been sourced elsewhere or generated by AI without human expertise. If it doesn’t, it needs strengthening.

Ensure your technical foundations are solid. Indexability, crawlability, and page experience aren’t prerequisites for traditional SEO only — they’re prerequisites for AI visibility. Pages that don’t serve snippets or can’t be crawled don’t exist for AI responses.

Invest in your Google Business Profile if you serve local customers. AI-generated local responses draw on this data, and an incomplete profile is a missed opportunity in both traditional and AI search.

Stop pursuing AI-specific workarounds. llms.txt files, chunking strategies, and manufactured mentions are not supported by Google’s own guidance. The time saved can be reinvested in content depth and genuine link earning.

Think about depth, not volume. Google is explicit that more pages do not equal better AI visibility. Fewer, more substantive pages that demonstrate real expertise consistently outperform volume strategies.

If you’d like help translating what Google’s guide means specifically for your site — whether that’s a technical audit, a content strategy review, or an assessment of your local presence — that’s exactly what we do. Google has given the industry a clear roadmap. The question now is how effectively you execute against it.