SGE in Google is not the end of SEO, but its evolution: how to adapt content and technical strategy

This is not a test anymore – SGE is being rolled out in full

In the summer of 2024, Google launched a large-scale rollout of Search Generative Experience (SGE). Although it is not officially available everywhere yet, AI responses are already being actively tested in the US, India, Japan, and Germany, and this is just the beginning.

Against this background, the old rumors have flared up again: “SEO is dead, all clicks will be taken by AI, horror.”

But it’s not true: SEO is not dead, it has just changed. It has changed before – for BERT, for voice search, for mobile-first. It’s just that now the content has to be ready for the fact that it’s not a human working with it, but an algorithm that tries to collect the answer for you.

What does SGE look like and why is it important

Search Generative Experience (SGE) is when an AI-generated snippet appears at the top of Google search results, briefly answering the query, and below it, the sources from which the answer was “collected”.

Is it bad for clicks? Not so good, but not the end of the world. After all, if your site is included in these sources, you will still be seen. And if you also mentioned the brand in the text natively, it’s a win-win.

SEO → GEO: what’s going on in general

With the introduction of Search Generative Experience, classic SEO as we used to work with it is no longer sufficient. Formally, technical factors, keyword optimization, page structure – all of this remains. But the very principle of “consumption” of your content is changing.

Users no longer have to go to the website to get an answer. AI simplifies this path for him. And that is why new approaches to optimization are emerging:

GEO (Generative Engine Optimization)

The focus is on how content is “perceived” not by a human but by a generative model. Relatively speaking, whether it can quickly extract a clear fact, definition, figure, argument from your page.

AEO (Answer Engine Optimization)

Optimization for systems that try not to provide a list of links but to form a ready-made answer. This is not only Google, but also Perplexity, Bing Copilot, ChatGPT-Search, and others.

What is changing in practice

1. Content structure

Content should be not just long, but logically built and easily structured:

• Clear title → meaning → detailed explanation;
• Paragraphs of 3-4 lines each;
• Use of subheadings H2-H3, numbered and bulleted lists/

2. Content that is “pulled”

AI does not read between the lines. It needs to:

• Wording in the style of “What is…”, “How does…”
• Direct answers to questions (Q&A-format)
• Definitions, brief conclusions, clear answers.

3. E-E-A-T as a technical standard

Google (and not only it) prefers content that demonstrates:

• Experience – real experience of the author or brand
• Expertise – expertise in the topic
• Authoritativeness – recognition, links, citations
• Trustworthiness – transparency of sources, accuracy of facts

Thus, an expert opinion with factual examples and validation has a much higher chance of being included in an AI response than a text with poor structure and vagueness.

GEO is the answer to the fact that AI becomes the first “reader” of your website. And if you want your pages to be visible in SGE AI results or cited in the responses of other systems, you should already review the structure, logic, and presentation of your content.

What really works: cases, not hypotheses

1. Geneva Worldwide

Geneva Worldwide is an American company with a 120-year history in the field of translation and language services.

Problem:

In the competitive market of simultaneous and video translation services, the company sought to improve its visibility on Google, in particular, to get into the new formats of AI Overviews.

What we did (GEO approach):
Conducted targeted optimization of the Video Remote Interpretation Services key page:

1. Content structure:
   – Instead of continuous text, we have implemented logically structured subsections: what is VRI, for whom it is suitable, how it works.
   – Each block answers a specific question.
   
2. Aliqui friendly formats:
   – Implemented bulleted lists that can be easily integrated into AI responses.
   – Added summaries after key sections – concise conclusions.
   
3. Semantics and FAQ:
   – We have implemented a FAQ block focused on user requests.
   – Added synonyms, clarifications, and wording that are usually entered in the search (for example, “how does video interpretation work”).
   
4. Technical support:
   – Optimized schema markup.
   – The page has been tested through Rich Results Test.

Result:
The page was included in Google’s AI Overviews block for relevant queries. This allowed us to get additional visibility without increasing advertising costs.

2. Scientific confirmation: +37% visibility in AI

American researcher Sanjay Rao and others have analyzed how content of different formats works in AI search engines (Perplexity, You.com, etc.).

What they found:
Content that contains facts, dates, numbers, and clear definitions is more likely to be used in AI answers.

Figure from the study: +37-40% visibility compared to plain text without it.

3. Single Grain

This is a digital agency from the United States, founded by one of the most recognizable marketers in the world, Neil Patel. The team regularly works with content, SEO, and lead generation for B2B and B2C businesses.

Their task was:
Adapt existing blog articles to the new search conditions so that the content could “catch” Google’s search engine results engine (SGE) and get into AI responses.<

What we did:

1. Content structure = “answer right away”
   Instead of the usual 300-word introductions and context, there is a single paragraph right below the headline with the exact answer to the query, as if for voice search: “Content marketing is a strategic approach focused on…”
2. Lists, facts, bullet points
   The main theses are not in a solid text, but in a form:
   • checklists;
   • bulleted lists;
   • short bullet points with confirmed numbers
3. Schema Markup
   We implemented structured data for each page to make it easier for Google to understand the content.
4. Updating headings and subheadings
   In H2 and H3, we used query wording, such as
   • “What is a content funnel?”
   • “How to create a high-performing blog strategy”

What we got:

• Articles started appearing more often in Google SGE snippets, even for queries that hadn’t previously generated organic traffic.
• Although organic conversions did not increase immediately, the brand’s AI visibility has grown significantly.

As a side effect, the general semantics of the blog has improved and the positions for long-tail queries, which are traditionally difficult to rank, have increased.

How to adapt your content

1. Start with the answer

No need for lyrical introductions that take up half the screen. Therefore, the first paragraph after H1 should give a brief, essentially, explanation of the request. Not an introduction, not a philosophy, but a definition or a specific answer.

For example:UGC (user-generated content) is content created by users, not by the brand: comments, photos, reviews, videos, etc.

2. Think like AI

For generative systems, it is not only what is written but also how it is structured that matters:

• Use logical H2/H3 that directly reflect the queries;
• Present each answer according to the scheme: title → essence → example → detail;
• FAQ blocks (Q&A format) significantly increase the chances of getting into SGE fragments;
• Visually separate lists, tables, quotes.

3. Content hubs

SGE (as well as classic SEO) values expertise and completeness of topic coverage.
The “pillar + cluster” model works better than random articles.

What it means:

• One large guide (pillar page) for 1500-2500 words;
• Plus 5-8 related materials on narrow sub-queries;
• Internal linking between them.

This is how the semantic core of the topic is formed, which AI reads as a complex authoritative block.

4. Visualization

Generative algorithms actively use not only text but also structured visual elements:

• Infographics allow AI to convey logic concisely;
• Tables and diagrams are easy to read and insert into a response;
• Labeled lists are a classic;
• Alt-texts, captions, image titles – all of this is taken into account as well.

About the technical part

Generative search does not cancel technical optimization. On the contrary, it becomes even more critical, because the algorithm “reads” your site directly, without a human as an intermediary.

1. Structured data (Schema Markup)

SGE actively uses Schema to generate answers.

The clearer the content is marked up, the more likely it is to be used as a part of the answer.

2. Speed and convenience = indexing

Google switched to mobile-first indexing a long time ago, and with the advent of SGE, loading speed and HTML cleanliness have become even more important:

• Core Web Vitals – layout stability, rendering speed, flicker-free interface;
• Progressive loading – a minimum of JS blocking, adaptability for different devices;
• Server optimization – AI will not wait for the page to be generated on the client.

New metrics: forget about CTR alone

You need to take into account:

• Whether you are in the SGE results;
• Whether AI mentions your website/brand name;
• Whether direct traffic is growing.

In other words, measure not only traffic but also influence.

And the main thing is not to panic

SGE is not a threat, but the next round of search evolution. Algorithms are changing the rules of the game, but the principle remains the same: useful, structured, authoritative content will always win.

Now, the winner is the one whose content is understandable not only to people but also to AI. The one who can not only write deeply but also present clearly. SGE does not kill SEO, but cuts off the superficial and multiplies the weight of the qualitative.

And if you want to stay in the focus of search in 2025, it’s time to optimize not for a keyword, but for a quality answer.