AI SEO is the practice of making your business visible everywhere search now happens: classic Google rankings, Google's AI Overviews, and the answers ChatGPT, Perplexity, and Copilot generate when someone asks them a question. Those AI answers aren't conjured from nothing. Assistants run web searches and build their responses from the pages that answer best, which means the work of being found and the work of being cited are the same craft, aimed at two outputs. AI SEO is that craft.
That's the full definition. The rest of this guide covers what changed about search, how the pile of acronyms fits together, what the work consists of, and how to tell the real thing from a rebrand.
What changed about search?
The interface, not the infrastructure. For twenty years, search meant typing keywords, getting a page of links, and doing the reading yourself. Now a growing share of questions get answered directly. Google puts an AI Overview above the results. ChatGPT, Perplexity, and Copilot skip the results page entirely and hand back a synthesized answer with a handful of source links. The person asking may never see a list of ten blue links at all.
That compression changes the economics of visibility in both directions:
- Fewer slots: a results page had ten positions and a second page nobody read. An AI answer cites a few sources and offers no page two.
- Better visitors: when an assistant does send someone your way, they arrive pre-sold. They clicked through from an answer that already recommended you.
One thing didn't change: the blue links still exist, people still click them, and they still convert. So the stakes went up while the openings shrank, and the job doubled. You're not just competing for a click anymore; you're competing to be the material the answer is made of. AI SEO covers both outputs at once, because as you'll see in a moment, they run on the same machinery.
How does an AI answer get built?
Mechanically, in four steps. Understanding them is the difference between doing this work on purpose and buying it on faith.
- The question becomes searches: one prompt fans out into several queries behind the scenes. "Best accountant for a small restaurant" might trigger searches on restaurant bookkeeping, local firms, and typical fees.
- Pages get retrieved from search indexes. Largely the same indexes classic SEO has always targeted.
- The model reads what it retrieved and pulls out the passages that address the question directly.
- An answer gets generated from those passages, citing the pages it leaned on.
Every step is a filter. Not indexed? You're out at step two. Indexed but burying your answer under 500 words of preamble? A clearer competitor gets extracted at step three. Vague where someone else is specific? You lose the citation at step four.
Notice what this implies: search visibility is upstream of AI visibility. There's no shortcut that gets you into AI answers while skipping the boring work of being findable. Which is why "AI SEO" has SEO in the name.
How do SEO, GEO, AEO, and LLMO fit together?
They're labels for one craft, coined from different angles:
- SEO is the umbrella: being visible in search, however search gets delivered.
- GEO (generative engine optimization) names the citation side specifically. We define it fully in what is GEO.
- AEO (answer engine optimization) is an earlier coinage for nearly the same idea, born in the featured-snippet era.
- LLMO (large language model optimization) is the same work again, named by people who like model-side framing.
The distinctions matter for reading industry chatter. They shouldn't matter for your invoice. An agency billing SEO, GEO, and AEO as three line items is charging you three times for overlapping hours. One competent program covers every acronym, because underneath the labels the deliverables converge: the same pages, the same structure, the same authority.
What does AI SEO work consist of?
Strip the jargon and it's four jobs:
- Answer-first pages. Put a direct, complete answer in the opening lines. Use question-shaped headings, short paragraphs, tables for comparisons, lists for steps. Models extract passages, so give them one worth extracting, and make it specific. Exact steps and exact definitions get cited; vibes get skipped.
- Entity work. Make your brand legible to machines: consistent name and facts across your site and profiles, schema markup, a clear page that says who you are and what you do. Assistants recommend brands they can identify without guessing.
- Reviews and corroboration. Models weigh what third parties say about you: reviews, mentions, citations from sites they already trust. This has to be earned. Astroturfed reviews and laundered mentions are liabilities wearing a growth costume, and we build our whole Reforge Method around refusing them.
- Measurement. Write down the questions your customers actually ask, the way they'd phrase them: "best family dentist near me that takes new patients," not "dentist keywords." Ask them in ChatGPT, Perplexity, and Google on a monthly schedule. Record who gets cited and recommended. A spreadsheet beats a proprietary score, because you can see exactly what it measures.
That's the whole trade. Everything a legitimate vendor sells maps onto one of those four. Anything that doesn't map deserves a hard question.
How do you tell real AI SEO from acronym theater?
The gold rush is on, and a lot of what's for sale is old work with a new sticker or, worse, no work at all. Four screens that catch most of it:
- Ask how they measure: real practitioners show you a repeatable test (these queries, these engines, this cadence, this spreadsheet). Theater shows you a dashboard with a trademarked visibility score and no methodology.
- Ask what the deliverables are: real answers sound like the four jobs above (pages rebuilt, schema shipped, placements earned, tests run). Theater sounds like "optimizing your AI presence."
- Ask what happens to your existing SEO: the right answer is that it's the foundation. Anyone pitching AI SEO as a replacement for search fundamentals is selling paint.
- Ask for the price: published pricing has to survive daylight and comparison. We publish ours for exactly that reason, and hidden pricing from a vendor is worth treating as information.
None of these screens requires expertise. They just require asking before you sign.
Where should you start?
With a baseline, this week. Write down 20 to 50 questions your customers ask when they're choosing someone like you. Ask each one in ChatGPT, Perplexity, and Google, in fresh sessions with no chat history. Record every brand and URL that shows up, yours and your competitors'. That's your current AI visibility, measured for real in an afternoon, and it costs nothing but the afternoon.
Then let the results pick your next move. Nowhere to be found? Start with indexing and answer-first rebuilds of your ten most important pages. Mentioned but described wrong? That's entity work. Present but losing to a competitor? Study the pages getting cited over yours and get more specific than they are. Run the same test again in 60 to 90 days, same questions, same engines, and you'll know whether any of it is working. Baseline first. Everything else follows from it.