SEO, AEO and GEO: what actually changes in the work?

What do the three terms mean?

SEO, search engine optimization, is the work that gets a page crawled, indexed and ranked in classic search results, and clicked once it is there. It covers technical health, content relevance and depth, and authority from links and mentions.

AEO, answer engine optimization, shapes content so a passage can be lifted whole as the answer to a question: featured snippets, People Also Ask boxes, voice assistants and AI summaries. The unit of optimization is the paragraph, not the page.

GEO, generative engine optimization, aims at the moment a generative model writes an answer and decides which sources to cite. It adds evidence density, freshness and off-site trust to the picture, because the model is choosing whom to believe, not just what is relevant.

Think of them as a funnel: SEO gets you into the index the engine reads, AEO makes your passages extractable, GEO makes the model pick you. Same web, same page, three scoreboards.

What does Google say?

Less than the industry wants it to. Google’s AI features documentation says AI Overviews and AI Mode use the same core systems as Search, that a page must be indexed and eligible for a snippet to appear, and that there are no additional requirements. Its 2025 post on succeeding in AI search repeats the same message: focus on unique, helpful content for people, and do not over-invest in structured data specifically for AI features.

Two practical rulings follow from Google’s own documents. The only way to opt out of Google’s AI features is the snippet controls, nosnippet or max-snippet, which also limit your normal snippets. Blocking the Google-Extended token affects Gemini training, not whether you appear in AI Overviews. People get both backwards.

What carries over unchanged?

Most of it. If the work was good SEO, it is good GEO.

• Crawlable, indexable, fast pages. Every engine fetches the page; some, like ChatGPT’s fetcher, give up quickly on slow ones.
• Server-rendered content. Text that only exists after JavaScript runs may rank in Google and still never be cited, because many fetchers do not execute scripts.
• Topical depth over scattered posts. A pillar that covers a subject completely, with spokes for the sub-questions, is exactly what fan-out retrieval rewards.
• Real authorship and real sources. Google’s helpful content guidance asks whether the page shows first-hand expertise and whether you would trust it. Engines that cite sources ask the same thing.
• Honest freshness. Update when something changed. Bumping a date without changing content is fake freshness and is detectable.

What actually changes?

Six things, in the order we change them on a site.

1. The unit becomes the passage

A page used to compete as a whole. Now each section competes as a 134 to 167 word chunk, and the opening 40 to 60 words under the heading carry most of the weight. So every H2 becomes a question in the words a buyer uses, and the first paragraph under it answers that question completely before anything else. Build to your point and the re-ranker never reads the point.

2. Sub-questions get their own answers

Engines expand one question into eight to twenty sub-queries: what it is, what it costs, how long it takes, how it compares, whether it is legitimate, what the alternatives are. Pages that rank for the sub-queries are cited far more often than pages that only rank for the head term. Most sites cover reformulations of the head term and skip the implicit and comparative questions. Cover them deliberately, aiming for most of the sub-topics, not all.

3. Evidence density goes up

Specific numbers, named entities, dated facts, a source link on each claim. The one controlled study on generative engine visibility found that adding statistics, quotations and citations lifted visibility substantially, while keyword stuffing reduced it. The study allowed invented facts; real work does not. The lever is genuine information, not the trick.

4. Format follows intent

Informational questions are cited from articles and definitions. Commercial questions, best, versus, alternatives, are cited overwhelmingly from listicles and comparison tables. A table with three states, yes, partial and no, and no more than four columns, is the most-cited format for comparison questions. Match the format to what the question is asking for.

5. Off-site mentions outweigh backlinks for AI

For classic Google authority, links still matter. For AI visibility, how often a brand is named on trusted third-party sites, linked or not, is the stronger signal, and most of the sources AI engines cite are third-party pages, not the brand’s own. Digital PR, review platforms, YouTube and community presence move the mention rate; the brand’s own site moves the citation rate. Both are needed.

6. The scoreboard splits

Rankings and clicks on one line. Citations per engine, from a fixed prompt library run several times per cycle, on another, with Google AI Overviews and AI Mode kept separate. Enquiries at the top, because they are the line that pays. How to build that instrument is in what AI search visibility is and how to measure it.

What should a business do first?

Check eligibility, then structure, then coverage, then mentions. Confirm the priority pages are indexed and snippet-eligible, that the search bots you want are allowed and the robots file has no stale user-agents, and that a Markdown twin or at least clean server-rendered HTML exists for each page. Rewrite the five most important pages into question-shaped sections with answer-first paragraphs. Map the sub-questions for each and fill the gaps. Then start earning mentions where the engines read.

That order is also the order of our AI search visibility engagements, built on the SEO foundation and fed by content and authority work. Three acronyms, one practice.