The development of widely available artificial intelligence and the related technological war between individual LLM models has revolutionized many branches of business.
Process automation, management of all company data, and, above all, content creation have all been turbocharged. Content has always been the foundation of website positioning, which means that SEO itself is undergoing a monumental transformation.
The SEO transformation associated with GEO is primarily due to changes in the way audiences search for and process content.
What does web searching look like today?
Just a few years ago, using search engines (which is essentially Google) was practically reflexive. If someone wanted to find a recipe for dinner, the answer to a biology question, or a review of a new phone, they would type a few words into the search bar and browse the results. Back then, the internet was an ocean of links, and users had to navigate between pages, compare sources, check publication dates, and draw their own conclusions.
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Above all, search engines didn't naturally understand human language; they instead analyzed keywords. You had to learn the "Google language," knowing how to formulate queries to get meaningful answers.
Example 1. Vacation plan
In the past, someone wanting to plan a vacation would type something like "cheap flights to Spain June 2020" or "best Barcelona hotel reviews" into Google and get a list of price comparison sites, travel blogs, and booking services. They had to browse several sources, read reviews, and sort through the offers themselves.
Today, such a query in a conversation with AI is more likely to sound like: "Help me plan a week-long trip to Spain in June, with a cheap flight and a nice hotel near the beach." The model can immediately suggest specific destinations, suggest cities, find approximate prices, and even write out a sample itinerary.
Example 2. Student Homework
Back in the day, a student searching for an answer to a question about photosynthesis would type "photosynthesis definition" or "how does photosynthesis work in plants?" Google would return links to pages from textbooks, Wikipedia, or educational blogs. You had to read a few articles yourself and extract the gist.
Today, the same question directed at AI might be: "Explain to me how photosynthesis works so I can understand it like a ten-year-old" or "Write a short explanation of photosynthesis for homework." In response, the user receives a simple, age-appropriate description, often with examples, comparisons, and even suggested illustrations.
In both cases, there's a fundamental difference: where once people sought information, today they seek meaning and ready-made understanding. AI not only points the way to knowledge, but in many situations it processes that knowledge itself and presents it in a form that previously required individual development.
From self-searching to ready-made answers
Change came gradually. First came intelligent suggestions, then voice assistants, and finally language models capable of conducting conversations and processing vast amounts of knowledge in a contextual manner.
Today, we increasingly no longer type queries into a search engine, but simply ask AI—just like a human. Instead of searching through dozens of pages, we expect a ready-made, sensibly structured answer. Not only has the tool changed, but also the way we think about information. Whereas it used to be about finding sources, now it's about finding meaning.
GEO, or Generative Engine Optimization
GEO is a way of optimizing website content so that language models (e.g. ChatGPT, Gemini, Claude, Perplexity and others) select a given website as one of the sources of answers provided to the user, and therefore recommend brands, products or services.
LLM in the context of search can be simplified into several main categories or channels:
- AI models, i.e. ChatGPT, Gemini, Claude, Grok, Perplexity and other LLM technologies
- AI Overview in Google and Bing, i.e. a special section above the search results
- AI Mode in Google, a separate tab that works on the basis of AI
Differences between SEO and GEO. What exactly is GEO?
In a nutshell:
- In SEO, you fight for your website to rank high in Google.
- W GEO you are fighting for the AI to recommend your company when someone asks, for example, "Where to buy original perfumes?"
In a sense, GEO is essentially the same as SEO: adapting content, technicalities, and link profiles to algorithmic requirements. While the principle is broadly the same, significant differences emerge in the details.
Content – still “content is king”
Currently, the importance of writing content in a natural question-and-answer format—as if speaking to an AI assistant—is growing. SEO specialists should ensure that their content answers specific user queries: "How do I do something?" "Why does something work?" "What's worth knowing about..."
The key is to create short, precise snippets—ideally around 40–60 words—that can be easily interpreted by language models and used in their responses. It's also worth separating content based on user intent, creating logical FAQ-type sections and grouping them into topic clusters.
Case studies based on data and specific conclusions from a given industry are also becoming increasingly important – it is precisely such materials that AI most often uses to strengthen the expert image of brands.
At the same time, it is necessary to analyze how publications on social media (e.g. LinkedIn, YouTube or Facebook) affect recognition and so-called social signals, which language models also take into account.
Technical optimization
In the technical area, the starting point should be a structured data audit. The SEO specialist must verify that the website has the correct schema markup on key subpages, such as products, blog posts, and categories.
Correctly implemented structured data helps search engines better understand a page's content and display it in a more engaging way, for example with ratings, prices, or FAQ sections in search results.
The next step is to ensure that the content is accessible to AI crawlers like GPTBot or Bingbot. SEO specialists should also verify the accuracy and completeness of JSON-LD markup (e.g., FAQPage, HowTo, Article, Product) using tools like Google Rich Results Test to help language models extract pre-made answer snippets.
Link building
Building off-site domain authority remains one of the pillars of effective SEO. A SEO specialist's task is to acquire valuable links from trusted sources—industry portals, expert publications, academic websites, and government websites.
It is also important to support the client in obtaining citations in reports, statistics and case studies, as this type of content is readily used by AI models as reference sources.
Thanks to this, the domain not only gains authority in the eyes of search engines, but also increases its chances of appearing in answers generated by artificial intelligence systems.
Challenges for marketers and SEO specialists
The era of language models (LLM), such as GPT or Gemini, presents marketers and SEO specialists with completely new challenges that change the way we think about online visibility.
Traditional SEO, based on keywords, meta tags, and links, is no longer the only point of reference. In generative models, which generate answers instead of results, trust and context, rather than page ranking, begin to play a key role. LLMs don't present dozens of links to choose from—they select one, synthesizing knowledge from various sources.
The challenge, then, is to design content that is credible, semantically consistent, and embedded in an expert context. LLM models favor sources with high authority, a consistent tone, and a clear information structure – therefore, SEO specialists must consider not only Google optimization but also how content is interpreted by AI systems.
An additional challenge is the lack of transparency in how models select their sources. Marketers can't see which sites have been included and which have been omitted. Therefore, they need to invest in building a broad digital footprint—from valuable publications to inclusion in industry reports and citations.
Ultimately, success in the LLM era requires more systemic thinking – not about how to “cheat” the algorithm, but how to become its natural choice, thanks to quality, credibility, and a consistent presence in the digital knowledge ecosystem.
Frequently asked questions about GEO positioning
GEO is a new branch of digital marketing and an evolution of traditional SEO. It involves optimizing and adapting a website's structure and content so that they are easily interpreted, selected, and cited by generative search engines and artificial intelligence models (e.g., Google AI Overviews, ChatGPT, Perplexity, Gemini, and Copilot).
- In traditional SEO, you fight to get your website as high up in the list of blue links in the search engine results pages (SERPs).
- In GEO, you compete for ranking among knowledge sources. The goal is for the AI to recognize your brand as the most credible and either directly recommend your business or quote your content in a synthetic response it generates.
The way internet users search for information is changing rapidly. Instead of browsing dozens of pages on Google, more and more users prefer to ask an AI chatbot a question and receive a ready-made summary. If your company isn't in the knowledge base used by AI, you're missing out on a significant portion of potential customers.
Artificial intelligence prioritizes specificity and unique value. Content should:
- Be written in natural, conversational language (Q&A style).
- Include hard facts, statistics and unique market insights (Information Gain), avoiding keyword stuffing.
- Be synthetic and easy to summarize by algorithms (clear definitions, bullet points, tables).
For language models, data structure is crucial for understanding context. In the GEO era, specialists must place particular emphasis on the advanced implementation of structured meta tags (e.g., JSON-LD format). These tags help AI robots accurately assign information about a company's products, authors, or services.
PromptRanker, Verseo's proprietary service, is a direct response to the GEO era. It's an expanded, comprehensive SEO package (both on- and off-page) that optimizes a website's visibility for AI tools and Google AI Overviews modules, securing a brand's position in the new search ecosystem.
Summary
The above article covers the following topics:
- What is the current operating model of internet search? The development of artificial intelligence and LLM models is revolutionizing business and forcing the transformation of SEO strategies towards GEO.
- Modern search has evolved from independently analyzing keywords in many sources to receiving ready-made, personalized answers and processed knowledge from AI.
- GEO is the process of optimizing content for AI modelsso that systems like ChatGPT or Gemini recommend a specific brand or website in their responses.
- How does GEO differ from SEO and how does it work? GEO involves tailoring your content, structured data, and link profile so that AI models recognize your site as a credible source and recommend it to users in their responses.
- What new tasks does the GEO era pose for specialists? The main challenge in the LLM era is to move away from simple website ranking towards building brand authority and credibility so that it becomes a natural source of knowledge chosen by AI systems.
