This emerging professional field still has no single, widely accepted name. AEO, GEO, LLMO, AI SEO, AI Search Optimization, and other terms are all in use. There is no clear agreement on whether they describe distinct practices or different aspects of the same developing field.
In my articles, I primarily use AI Search Optimization. I don’t consider the alternatives wrong, and I don’t think the terminology debate has been settled. It’s simply the working term I’ve chosen, and there are reasons behind that choice.
One Field, Several Names
AEO — Answer Engine Optimization — focuses on the answer. Instead of only providing links, a system can respond directly to a user’s question.
GEO — Generative Engine Optimization — frames the practice around the generative nature of these systems. The term also has a strong academic foundation. In 2023, researchers from Princeton University, Georgia Tech, the Allen Institute for AI, and IIT Delhi introduced GEO in the paper “GEO: Generative Engine Optimization” as an approach to improving content visibility in generative engine responses.
LLMO — Large Language Model Optimization — shifts the focus to the large language models behind many of today’s AI systems.
AI SEO connects the emerging practice more directly to the development or extension of Search Engine Optimization.
Each name has a reasonable logic behind it. What remains unsettled is how these concepts relate to one another.
Ahrefs, for example, uses GEO as its primary term while noting that the practice is also known as AEO or LLMO. [Ahrefs — Generative Engine Optimization]
Search Engine Land takes a different approach. It draws clearer distinctions between SEO, AEO, GEO, and LLMO and associates them with different forms of search and AI visibility. [Search Engine Land — What Is LLMO?]
There are also attempts to find a broader name. Some practitioners and specialist terminology resources use AI Search Optimization as an umbrella term for improving visibility across AI Search, including work that others describe as AEO or GEO. [AISO System — AISO vs SEO] [GEO Compass — AI Search Optimization]
These competing classifications say something about the state of the profession itself. The field is taking shape, but its boundaries and vocabulary are still evolving.
For me, that makes the more interesting question:
What exactly are we trying to name?
Why I Start With Search
All of these terms capture real aspects of what is changing. But when choosing a general name for the field, I find it useful to look at it from the user’s perspective.
Increasingly, a user sees a single AI interface and brings a task to it. What happens behind that interface is usually secondary.
The system may combine language models, web search, retrieval, ranking, external sources, and other tools. A recent academic review of GEO describes generative search as a multi-stage process involving search activation, crawling and indexing, retrieval, reranking, citation, generation, and other stages. [Optimizing Visibility in Generative Engines: A Critical Survey of GEO, 2023–2026]
The technology is becoming more complex, while the user experience is becoming more unified.
That is why defining the whole field around one particular component of the system feels increasingly limiting to me.
Search Doesn’t Have to Look Like Search Anymore
The way people search is changing too.
A user might ask:
“Which CRM is best for a small accounting firm?”
That clearly looks like a search query.
But the same person might say:
“I’m opening an accounting firm with five employees. Which CRM would you choose for me?”
Now the interaction involves conversation, comparison, and recommendation. The underlying information need, however, is much the same: the person is looking for a suitable solution.
With AI Search, search is no longer defined by the shape of a query or a results page filled with links. Through a conversation with an AI assistant, people can look for information, companies, products, services, options, and recommendations.
In that sense, search is becoming broader than the search query itself.
Why AI Search Optimization
This is why I use the term AI Search Optimization.
It names the field after the broader activity — AI Search — without tying that name to one technology within the system or one particular form of output.
Generative AI will evolve. Language model architectures will change. So will the ways AI systems find and synthesise information. The underlying user needs are more durable: finding information, comparing options, discovering companies and products, getting recommendations, and making decisions.
For me, the logic is straightforward:
AI Search → AI Search Optimization.
It also makes the term less dependent on whichever technology happens to be at the centre of attention today. AI assistants may work very differently a few years from now, while AI Search may still describe what people use them for.
An Umbrella Term — Within My Own Terminology
In this blog, I use AI Search Optimization as an umbrella term for the professional practice concerned with visibility in AI Search.
I am not suggesting that AEO, GEO, and LLMO are officially subcategories of AI Search Optimization. There is no generally accepted classification of that kind today.
The other terms remain useful. GEO may be more precise when discussing generative engines, AEO when the focus is direct answers, and LLMO when the subject is specifically large language models.
When I talk about the field as a whole, though, AI Search Optimization best matches the way I currently understand it.
A Working Term, Not a Final Answer
The professional community may eventually settle on GEO, AI SEO, AI Search Optimization, or something else entirely.
If a stable consensus emerges, there is little reason to resist it. Terminology exists to make communication easier, not to win arguments over acronyms.
I’m not suggesting that everyone should use AI Search Optimization. I’m explaining why I use it today.
The term itself doesn’t have to last forever. AI Search is still developing, and the boundaries of the profession — along with the language we use to describe it — will develop with it.
For now, AI Search Optimization is the working term that most accurately describes the field I write about.
