AEO vs GEO vs SEO: what’s actually different in 2026

Three acronyms make it sound like you need three strategies, three budgets and probably three agencies. You don’t.

Most of what gets sold as GEO is good SEO with a new name. The work that actually moves AI answers, getting your brand talked about on other people’s pages, is usually missing from the package. This guide explains what each term means, what to keep doing, what to change, and how to split your time.

What SEO, AEO and GEO mean

GEO comes from a 2023 research paper that coined the term and found content changes could lift a page’s visibility in AI answers by up to 40%. AEO is the older idea of optimising to be the answer rather than one of ten links. You’ll also see “AI SEO” and “LLM SEO”. For planning and buying, treat AEO, GEO and AI SEO as one thing: getting into AI answers.

What stays the same

For Google’s own AI features, the answer is official. Google says there are “no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary”. A page needs to be indexed and eligible to show a snippet. You don’t need special files or markup.

So this SEO checklist does double duty. Keep doing all of it:

• Crawlable and indexed. Clean robots.txt, an XML sitemap, no important pages blocked.
• Text in the HTML. Key content visible without JavaScript (check with view-source).
• One page per question. A clear page for each thing buyers ask, not one page that mentions everything.
• Answer first. The direct answer in the first two sentences, then the detail.
• Fast and mobile-friendly. Same as always.
• Updated dates. Keep important pages current and show when they were updated.

Google also explains the one mechanical twist: AI Overviews and AI Mode use “query fan-out”, running several related searches to build one answer. Your page can be cited for a sub-question you never targeted, which rewards pages that answer specific questions cleanly.

What you can skip: llms.txt files (four studies found AI crawlers almost never read them) and schema markup as an AI tactic (Ahrefs found adding it didn’t lift AI citations).

Difference 1: What happens off your site matters more

This is the big one. A University of Toronto study compared Google with GPT-4o, Claude, Perplexity and Gemini on 1,000 ranking-style queries. The AI engines’ cited domains barely overlapped Google’s top 10: 4.0% on average for GPT-4o, 11.1% for Gemini, 12.6% for Claude and 15.2% for Perplexity. Ranking first on Google doesn’t put you in the AI answer.

The AI engines also lean much harder on independent sources. Share of cited sources by type, across consumer-electronics queries:

Ahrefs’ study of 75,000 brands points the same way: branded web mentions correlated 0.664 with visibility in AI Overviews, three times more than backlinks (0.218).

What to do about it:

1. Find the review sites, comparison articles and “best X” lists that AI cites for your category (run your buyers’ questions in ChatGPT and Perplexity and click the sources).
2. Get onto those pages: pitch the authors, earn reviews, offer data they can use.
3. Show up in the community threads where your category is discussed, especially on Reddit, which was the single most-cited domain in Profound’s analysis of AI citations. Read why Reddit posts get removed first.
4. Aim for a steady flow of new third-party mentions every month, not one launch-week spike.

Difference 2: You plan around prompts, not just keywords

People type keywords into Google. They talk to ChatGPT. The same buying intent looks very different in each, and the prompt version tells you exactly what page to write:

Build a list of 20–30 prompts from sales calls, support tickets and Reddit thread titles. Keep your keyword research too: AI answers are assembled from searches, so the pages that rank for those sub-searches still matter. Our ChatGPT citation playbook walks through building the list.

Difference 3: Clicks aren’t the whole scoreboard anymore

Ahrefs compared 300,000 keywords in December 2025: when an AI Overview appears, the top-ranking page gets 58% fewer clicks than expected. A buyer can read your name in an AI answer, never click, and search for you directly a week later. Your SEO report won’t show that.

Report these side by side every month:

Keep mentions and linked citations on separate lines. They’re different results: you can be named without a link, or linked without being recommended.

A smaller difference: freshness counts for more

The same Toronto study measured how old cited pages were. For consumer-electronics queries, the median cited page was 79.8 days old for GPT-4o and 62.3 for Claude, against 130.4 days for Google. In automotive the gap was wider still. Update your comparison, pricing and “best X” pages at least every quarter, and show the date.

A practical routine: keep a list of your 10 most important answer pages, put a quarterly reminder in the calendar, and on each pass update prices, screenshots and anything a competitor has changed. Change the visible “updated” date only when the content genuinely changed. A page that says it was updated yesterday but still quotes last year’s prices does more harm than an honest older date.

Do you need a different plan for each AI engine?

Mostly no, but they don’t behave identically. In the Toronto study, each engine overlapped Google’s top 10 results to a different degree, and leaned on different kinds of sources:

The practical takeaway: one plan covers all of them, as long as it includes both strong answer pages on your site and mentions on independent sites. Test your prompts in at least ChatGPT and Perplexity each month, because they often disagree, and the gaps between them show you which half of the plan needs work.

How to split your time

For a small team with an SEO foundation already in place, here’s a reasonable starting split. Adjust once you see where you’re missing:

If you have no SEO foundation yet, flip the first month: fix technical access and publish your core answer pages before you start outreach.

Questions to ask anyone selling you GEO

1. Which prompts will you track, and can I see the list before we start?
2. Will you report brand mentions and linked citations separately?
3. How do you get us mentioned on third-party sites, specifically?
4. What do you do on Reddit and communities, and how do you avoid getting removed?
5. What on-page work is different from normal SEO, and why?
6. Do you recommend llms.txt or schema as AI tactics? (If yes, ask for the evidence.)
7. How do you test prompts so personalisation doesn’t skew the results?
8. What should we expect to see by month 3?

Good answers are specific and talk about prompts, pages and third-party mentions. Vague answers about “AI-optimised content” are SEO with a new invoice line.

Common mistakes

• Pausing SEO to “do GEO”. AI answers are built from pages that are crawlable, indexed and ranking for the sub-searches behind a prompt. Drop SEO and you drop out of both.
• Rewriting every page “for AI”. Clear, answer-first pages already work for both. Rewrite the pages that answer buying questions first and leave the rest.
• Spending everything on your own site. The AI engines in the Toronto study took most of their citations from independent sites. If none of your budget goes off-site, you’re missing the biggest lever.
• Tracking AI visibility from your own account. ChatGPT personalises answers to your history. Test logged out or in a temporary chat.
• Reporting one blended “AI visibility score”. A single number hides whether you’re being named, linked, or neither. Keep mentions, citations and clicks separate.
• Buying three services. One team that covers on-page, off-site and measurement beats three that each assume the others are doing the hard part.

Your 90-day plan

AEO vs GEO vs SEO comes down to this: the same on-page job, plus two things SEO never asked of you. Be talked about on other people’s pages, and measure whether you’re named and cited, not only whether you’re clicked. Keep your SEO, add those, and you’ve covered all three acronyms.