SEO, GEO, AEO, and AIO: online search has a new vocabulary
Our industry has a real passion for acronyms. We have been collecting them for over twenty years, but in recent months we have been overwhelmed by a wave of definitions that seek to bring order to the chaos brought about by artificial intelligence.
These labels actually conceal a very “human” meaning: every time the way people search – or search engines respond – changes, we need something to describe and define it better. To be less afraid of the new.
Often, however, the effect is the opposite: GEO, AEO, AIO, LLMO, SXO, and other acronyms are creating a sense of disorientation. On closer inspection, however, they do not define “new disciplines,” but rather different ways of addressing the same need: understanding how to make a brand visible, cited, and credible. This is the goal of SEO, which therefore remains at the center of this evolution and expands its scope to include these new search spaces, shifting to systems driven by artificial intelligence. In short: the acronyms change and multiply, the direction remains the same, but we all need to speak the same language in order not to lose clarity.
GEO, AIO, AEO: what the new SEO acronyms really mean
If you work in digital, you will have come across them all: SXO, AEO, AIO, GEO, SEO for AI… each one promises to herald a “new era” in the pursuit of visibility.
In reality, each new acronym that populates our vocabulary describes a specific angle of the work, a specific goal within a larger, interconnected system. They are all different nuances of the same path: the transition from a search made up of links and rankings to a search made up of experiences, answers, and language models.
When the way people search or the engine interprets responses changes, the language we use to describe it also changes. This is how terms such as SXO came about—when the user experience became an integral part of positioning—or AEO, when the goal was no longer “to be found” but “to respond first.”
Today, with the arrival of generative engines and synthetic responses, the same logic has been repeated: GEO, AIO, LLMO, and AI SEO are the new acronyms for a search ecosystem that no longer stops at SERP. These are signs of adaptation: the lexicon is changing because SEO is expanding, incorporating artificial intelligence and touching on communication, reputation, content, and technology all at once.
And even if we prefer to focus on strategy rather than the name of the activity, it is useful to have a small guide to the acronyms one by one, to understand what they really mean and where they intersect.
This acronym best describes the new phase of SEO. The goal of GEO is to become the source of AI. This practice aims to ensure that your content is read, understood, and cited by engines based on generative AI — such as Google’s AI Overview, ChatGPT, Gemini, or Perplexity.
In this scenario, ‘appearing’ has two meanings. First, being in the model’s memory, thus being part of what it has learned: useful for the future, almost never visible, without citations. Second, entering real-time retrieval and ending up in the response with an explicit source, as happens in AI Overview or in generative engines that cite pages.
True GEO works mainly on this second level because it is observable and depends on your online presence and reputation. It works when you exist in searches, when the content responds accurately, and when the page is recognizable as a source.
Think of it as the next step after SEO. You position yourself, then take care of structure, clarity, and verifiability so that, at the moment of synthesis, your page is chosen and cited.
- AIO – Artificial Intelligence Optimization
It is an umbrella term that encompasses all strategies, including AEO and GEO, aimed at making a brand’s content and data easily interpretable, reliable, and usable by any artificial intelligence system.
It is actually a “hybrid” acronym, because it can indicate two complementary directions:
- Using artificial intelligence to optimize and do SEO more efficiently (automating analysis, writing, clustering, insights).
- Optimizing for artificial intelligence, i.e., building content that algorithms can read and interpret correctly.
In the first case, it refers to method, in the second to visibility. In both cases, it represents the definitive convergence between technology and strategy, between SEO and AI, considering the readability and consistency of content for both people and machines.
There is also another meaning of the term, which is a contraction of AI Overview, the Google Search feature that provides answers summarized from indexed content. In short, the context in which the acronym appears is very important here.
- AEO – Answer Engine Optimization
This acronym has been around for years and is now back in vogue. It originated when search engines began to give direct answers instead of lists of links – and the goal, for you, was to be the content that responded first, in a comprehensive and concise manner.
With AI engines, this logic is amplified: this specialization focuses on optimizing content to provide a direct answer to a specific user question, found in spaces such as AI Overview, AI engine responses, replies provided by voice assistants, or featured snippets.
In concrete terms, it is an invitation to structure texts around questions and sub-questions, as in the “People also ask” boxes, which is the basis for being selected in generative responses as well. AEO often intercepts so-called “zero-click searches,” scenarios in which the user gets the solution they are looking for without visiting a web page, and in which the brand still gains visibility and authority.
- SXO – Search Experience Optimization
It suggests a change of perspective: SEO that also measures the user experience, not just the position in SERP. The idea is that visibility is of little use if the page does not really satisfy those who visit it, if it does not transform the contact into a useful, fluid, and satisfying interaction.
With AI interpreting intentions and evaluating content relevance, SXO is now back in the spotlight: perceived quality becomes an integral part of ranking, even for generative engines. And with the reduction in clicks, optimizing the experience becomes crucial to maximizing the value of each visit, strengthening the relationship with the brand, and guiding the user towards conversion.
- LLMO – Large Language Model Optimization
This is the most technical part of the whole group, born out of research. Large Language Model Optimization studies how language models (LLMs) retrieve and interpret information in their retrieval processes. It refers to a more technical and in-depth optimization, focused on adapting content in terms of structure, semantics, and data for systems that respond, not just list.
The aim is to make them perfectly “digestible” by the language models that power AI systems, facilitating the processes of extracting, understanding, and reusing information to generate accurate and consistent responses.
- AI SEO – Artificial Intelligence SEO
This is the formula many companies use to describe SEO “enhanced” by artificial intelligence.
It refers to a different way of working, where human skills and generative models coexist in a continuous optimization flow: using AI to analyze trends, create drafts, cluster intentions, or measure content potential. The difference is always made by the ability to read data and use it to build strategies.
This concept was introduced by Ivano Di Biasi back in 2024, when most generative engines were still in the experimental phase.
It means preparing content so that AI can understand, cite, and use it in its responses. It anticipates the logic of GEO and frames it in a broader way: writing to be understood, cited, and used by language models, as well as by traditional SERPs. It is a formula that perfectly sums up the ultimate goal of contemporary SEO, which is to ensure that content is not only found but also understood by artificial intelligence.
Why all these acronyms are being created
Yes, they may seem like mere linguistic gimmicks, but the truth is that acronyms serve to give shape to something that is changing faster than words, namely the way in which visibility is constructed.
Think about it: for years, the model was linear. A user would formulate a query, often using keywords, and the engine would return a list of blue links to choose from. The competition for visibility was played out entirely on the ability to rank at the top of that list.
Now this pattern has been flanked and partly replaced by a more complex interaction, in which people address search engines (and this plural form already says a lot!) in a conversational way, asking questions articulated in natural language, as if they were talking to an assistant. They expect to receive a direct and concise answer, not just a list of sources to consult. And the systems used are no longer just “search engines,” but “response engines” capable of understanding, reworking, and synthesizing the information on the web to build a new output. This has created a new competitive space, the response itself generated by AI, which exists before and sometimes in place of the click to an external site.
The numbers confirm this: AI Overview has already redesigned traffic distribution, reducing the click-through rate of the first organic position by up to 34.5%. From a broader perspective, Gartner predicts that by 2026, the volume of searches on traditional engines will decline by 25%, precisely because of the shift of users to generative platforms—even though, for now, Google exceeds ChatGPT’s search volume by 210 times.
The new acronyms were born precisely from the need to name the strategies necessary to oversee this new and fundamental level of online visibility. As mentioned, the reason is linked to our human nature—acronyms are reassuring, they bring order to chaos, they give the impression of mastering a phenomenon that is still evolving—and in some cases also to a utilitarian logic—sometimes, this fragmentation of the lexicon shifts the focus from the fundamental principles of our work (identifying a need and providing the best possible resource) to chasing the latest trendy acronym.
A single discipline, new horizons: it’s all SEO (Search Everywhere Optimization)
For us, behind the acronyms, the logic remains the same: understanding how people formulate their questions and how systems, whether human or artificial, choose who to entrust with the answers.
The fragmentation of vocabulary may suggest that AEO, GEO, and SXO are separate disciplines, alternatives to traditional SEO. This view is superficial and inaccurate, because we are witnessing an expansion, not a replacement. SEO remains the core skill set from which everything else develops: GEO looks at generative engines, AEO at direct answers, SXO at user experience, and AIO at the use of artificial intelligence in the optimization process. Everything revolves around the same principle: making content understandable, relevant, and reliable for those who search and those who process the answers.
To use a metaphor, SEO is the art of driving: it teaches the fundamentals of control, strategy, and safety. AEO, GEO, and SXO are the specializations needed to drive different vehicles on specific terrains: optimizing for a direct answer (AEO) is like driving a race car on a circuit, where speed and precision are everything; being cited by a generative engine (GEO) is more like an off-road rally, where endurance, reliability, and adaptability are needed; curating the experience (SXO) is like driving a tour bus, where passenger comfort and satisfaction are the main goals. The vehicles and terrains change, but the fundamental driving skills remain the same.
The key point, in fact, is that the only optimization activities for artificial intelligence that offer concrete results today are based on a non-negotiable assumption: visibility on traditional search engines. When a generative engine such as ChatGPT or Perplexity does not know an answer because the information is too recent (it exceeds its knowledge cut-off), it activates a real-time search process (RAG) by querying Google or Bing. The same applies to Google’s AI Overview, which by its very nature is always the result of a synthesis of sources taken from the SERP. This means that in order to be chosen, cited, and mentioned by an AI, you must first be ranked on Google. If your content is not visible and authoritative in traditional search, it will never be “picked up” by artificial intelligence to build its response. This is where the apparent complexity is simplified: it’s all SEO, because SEO remains the engine that powers visibility in these new spaces.
For this very reason, it makes more sense today to reinterpret the acronym SEO as Search Everywhere Optimization. This new interpretation, which we have adopted at SEOZoom, better describes the current reality. Optimization is no longer confined to SERPs, but must extend to the entire ecosystem in which people search for and find answers—generative engines, social media, marketplaces, voice assistants. The foundations remain those of the SEO we know, but they apply to a much broader and more interconnected field of action.
