SEO vs. AEO vs. Geo vs. AIO: Same Work, Different Acronyms

The proliferation of acronyms such as AEO, GEO, AIO, LLMO, and AI SEO describes the same underlying practice of optimizing content for AI-driven answer engines, differing mainly in branding rather than technique, according to an analysis by Canonry. The article argues that SEO is not dead but extended, with traditional technical elements like structured data and crawlability remaining essential, and notes that a 2023 GEO paper reported visibility gains of up to 40 percent from adding citations and hard numbers, though gains vary by domain.

Someone asks what we do. I say answer engine optimization. They say "oh, GEO." Their agency calls it AI SEO. A vendor pitched them LLMO last week. All three of them read a post that morning explaining that SEO is dead. The acronyms are multiplying much faster than the field underneath them is. Most of the naming is positioning rather than description, which leaves a business owner trying to tell a real technical claim from a vendor staking out territory, using nothing but the vocabulary the vendor chose. The terms, and where they came from | Term | Expands to | Where it came from | |---|---|---| AEO | Answer Engine Optimization | Predates LLM chat. Used for featured snippets, "position zero," and voice assistants. | GEO | Generative Engine Optimization | A 2023 paper, | AIO LLMO AI SEO Two of these have real histories. AEO was in use before ChatGPT existed, describing the work of getting your content lifted into a direct answer instead of a blue link. GEO came out of a peer reviewed paper, which is more than most of the vocabulary in this field can claim. The rest are flags planted on ground that was already occupied, which is less a moral failing than the predictable result of a category forming before anyone owns the dictionary. They differ in origin, not in practice Put an AEO checklist next to a GEO checklist next to an AI SEO checklist. You will get the same list: structured data, entity consistency, extractable HTML, question shaped headings, a direct answer in the first sentence under each heading, real sources, honest freshness signals. If two frameworks prescribe the same work and measure the same outcome, the difference between them is branding. The GEO paper is genuinely worth reading, and I would rather someone cite it than the average LinkedIn thread, but what it actually contains is a study of which content edits pay off. The authors built a benchmark of queries across several domains, ran edits against it, and reported visibility gains of up to 40 percent, with the strongest results from adding citations, quotations, and hard numbers. They also found the gains swing by domain, which is the part almost nobody repeats when they cite the 40 percent. All of that is a ranking of tactics inside a practice people were already doing. SEO is not being replaced, it is being extended The loudest piece of misinformation in this space is "SEO is dead." Look at what still has to be true before an AI answer can name you. Your page has to be crawlable and indexable. It has to render without waiting on a pile of JavaScript. It has to carry a canonical, a title, headings, and alt text. It has to come from a domain with some authority behind it. The highest weighted signal in our own 16 factor onsite model /blog/what-is-answer-engine-optimization is JSON-LD structured data, which is SEO engineering that predates the first public LLM chat interface by years. What actually changed is the unit of measurement. SEO measures a position in a list. AEO measures presence in a paragraph. There is no page two of a generated answer, and there is no position 7 that still leaks a little traffic. In one Canonry dataset covering 11 keywords over 66 runs, the split was binary: branded queries where the business had content got cited 82 to 90 percent of the time, and informational queries where it had none got cited 0 percent of the time. Nothing in between. So "SEO versus AEO" is the wrong frame to begin with. SEO expanded onto a surface that does not produce a ranked list, and the old scoreboard simply cannot read the new one. The distinction that is actually real None of these acronyms name the two splits that matter technically. The first is whether a model knows you from its training data or fetches you at answer time. We can observe the second. A fetch leaves a line in your server logs /blog/ai-traffic-server-logs with a user agent attached, and a retrieved page often leaves a link in the answer. We cannot directly observe the first. Any confident claim about what is or is not in a model's weights is inference, not measurement, and it should be labeled that way. The second is mention versus citation. A model can name your business without linking to you, and it can link to you without naming you. These are two separate signals and neither can be computed from the other. Most dashboards collapse them into one "visibility" number, which is exactly the kind of tidiness that hides what is actually happening /blog/ai-visibility-tools-are-lying . Sorting out those two questions for your own site will tell you more than any amount of arguing about what to call the work. Four questions that filter the noise Does the claim name a mechanism? "AI prefers fresh content" with no fetch, no schema, no observed behavior behind it is a vibe. Ask which crawler, which page, which observed change. Does it separate mention from citation? If a tool reports one number, ask which one it is measuring. If the answer is "both," it is measuring neither cleanly. Does it promise a rank? There is no rank on this surface. Same prompt, different run, different set of names. Is it repeated across providers? One screenshot of one ChatGPT answer is an anecdote. Answers move run to run, and ChatGPT, Gemini, Claude, and Perplexity retrieve differently enough that a result on one says little about the others. In my experience most of what circulates fails on the first question, and once a claim has no mechanism behind it the other three rarely get a chance to matter. Pick one word and measure it We say AEO because it names the thing that changed, which is that the output is an answer and not a list. If the industry converges on GEO next year, we will write GEO on everything and nothing about the work will change. What you call it is not the decision. The decision is whether, for the queries your customers actually type, you can say whether the answer named you and whether it linked to you. Run the audit /audit to find out if your pages are even readable to the thing generating those answers, then track the answers themselves over a few months. Whichever acronym wins by then, that measurement is the same.