What Did Google Just Say About AEO and GEO in 2026?

What did Google just say about AEO and GEO?

Google now treats answer engine optimization and generative engine optimization as part of SEO, not separate jobs. In its 2026 Search Central guide on generative AI features, Google says optimizing for AI search is "optimizing for the search experience, and thus still SEO." That is one discipline, not three competing playbooks.

I have watched this debate get loud over the past year. Vendors sell "AEO packages" and "GEO audits" like they are brand new skills. So when Google published a plain guide saying the opposite, it mattered. I want to walk you through what the guide actually says and where I think it is right and where it is incomplete.

Short version: the fundamentals you already know still carry most of the weight. But Google only speaks for Google, and that caveat is the whole game.

What is inside Google's new AI optimization guide?

The guide is Google's official page on optimizing for generative AI features like AI Overviews and AI Mode. Its core message is that no special AI strategy is needed. Google says its AI features are "rooted in our core Search ranking and quality systems," so the same content and technical quality that helps you rank still applies.

Google also explains how those features find your pages. The guide says AI Overviews and AI Mode use retrieval augmented generation and a technique called query fan-out. In plain terms, Google breaks one question into many smaller searches, pulls passages from its index, and stitches an answer together. Your page has to be in that index and worth pulling.

This is why I keep telling clients the boring work is the work. If your site is slow, thin, or hard to crawl, no AEO trick saves it. Google is telling you the front door and the side door lead to the same room.

Does this mean AEO and GEO are dead?

No. The labels are fine as shorthand. What Google is pushing back on is the idea that AI search needs a separate technical stack. Google says the best practices for regular Search still apply to its AI features, with no extra requirements to appear in them. The strategy did not split into three. It stayed one.

Here is my honest take. AEO and GEO are useful words for a real shift in behavior. People now read an answer instead of clicking ten blue links. That changes how you write and what you measure. But it does not mean you rebuild your site for robots. It means you write clearly enough that both a person and a model can lift your point in one clean sentence.

If you want the mechanics of that, I wrote about how an AI engine decides which sentence to quote. The gist is the same as Google's: clarity beats tricks.

Why does Google say you do not need llms.txt or special schema?

Google's guide says llms.txt, content chunking, AI-specific rewriting, and special schema are not needed for its generative AI features. Google reads your normal HTML the same way it always has. It does not look for a separate file to feed its models. That is a direct statement from the vendor, so I take it at face value for Google.

This surprised a lot of people, because llms.txt has been sold hard as a must-have. I still think llms.txt has a place for some AI tools that choose to read it. But for Google Search specifically, the guide is clear that it does nothing. Do not add work that the platform itself says it ignores.

The lesson I draw is simple. When a platform publishes its own rules, believe the platform over the hype. Press coverage and hot takes are not the source. The docs are.

Does structured data still matter for AI search?

Partly. Google's guide says structured data is not required for generative AI search, and there is no special schema.org markup to add. But Google still recommends structured data for your overall SEO, because it keeps you eligible for rich results in normal Search. Schema is not an AI tactic. It is a Search tactic that still pays off.

I get asked this weekly, so let me be blunt. Do not add schema hoping it will bribe an AI Overview into citing you. That is not how it works. Add schema because it can win you review stars, FAQ rich results, and clearer entity signals in classic Search.

If you are weighing whether a specific type is worth it, I covered the trade-off in whether you should still add FAQ schema in Webflow. Same principle applies here.

What is commodity content, and why does Google keep warning about it?

Commodity content is writing that repeats what everyone already says. Google's guide draws a line between commodity content and content with unique insight beyond common knowledge. The message is that AI features favor pages that add something, not pages that restate the obvious. If a model can already generate your paragraph, it will not need to cite you.

This is the part I care about most. An answer engine is a summarizer. If your page is a summary of summaries, you are competing with the machine at its own job and you will lose. The only durable edge is a real opinion, a real number from your own work, or a real lesson you paid for.

That is the whole reason I publish my own pricing, my own mistakes, and my own client patterns. Not because it is brave, but because it is the one thing a language model cannot copy from someone else.

Does Google's advice cover ChatGPT and Perplexity too?

No, and this is the caveat that matters. Google's guide speaks for Google Search, which powers AI Overviews and AI Mode. It says nothing about ChatGPT, Perplexity, Gemini as a standalone app, or Microsoft Copilot. Each of those systems has its own retrieval sources and its own habits, so "still SEO" is only half the picture.

OpenAI's ChatGPT and Perplexity, for example, often lean on different sources than Google's index. They may weigh community sites, licensed data, or their own crawl. So the content quality that helps you in Google can help you there too, but the citation behavior is not identical across engines.

My working rule is this. Optimize for Google's AI features exactly the way Google says, because Google told you. Then treat other engines as separate audiences you study on their own terms. I dug into one version of this in why ChatGPT cites Reddit instead of your website.

How does Google actually pull your content into AI Overviews and AI Mode?

Through your normal index listing. Google's guide explains that AI Overviews and AI Mode run on retrieval augmented generation and query fan-out over the Search index. So the page has to be crawlable, indexed, and strong on the underlying query. There is no separate AI index you submit to. The path in is the path you already know.

What this tells me is where to spend time. Get the crawl clean. Get the page indexed. Make the answer to the core question easy to find near the top. Then make sure the surrounding content proves you actually know the topic, because query fan-out will test you on the neighboring questions too.

None of that is exotic. It is the same technical hygiene I would run for any Webflow site I build, just aimed at a surface that reads your work instead of only linking to it.

What should you do next?

Trust the source over the noise. Read Google's own guide, keep your core SEO strong, and drop any AI-only busywork Google says it ignores. Then invest the saved hours in content only you can write. That is the move that works for both classic Search and AI features.

If you want a second set of eyes on whether your pages are commodity or genuinely useful, that is the kind of review I do every week. I am Pravin, an AEO and GEO specialist in Bengaluru, and I would rather tell you the honest answer than sell you a package Google says you do not need. Reach out at pravinkumar.co and let's chat about your site.