GEO vs AEO vs SEO: what’s different and what to do

What do SEO, AEO and GEO mean?

SEO, search engine optimization, is the work of ranking pages in search results and earning the click. AEO, answer engine optimization, focuses on being the direct answer: the featured snippet, the voice answer, the cited source in an AI answer box. GEO, generative engine optimization, focuses on being named or cited inside answers that a language model writes, in ChatGPT, Perplexity, Gemini, Claude or Google’s AI Overviews and AI Mode.

In practice the last two overlap so much that many teams use them interchangeably. The useful distinction is between earning a ranking and earning a mention.

What do they have in common?

More than the acronyms suggest. Google’s May 2026 guide to optimizing for its generative AI features says SEO best practices remain relevant because those features are rooted in its core ranking and quality systems, and that no special markup or AI-only file is required. A page that is crawlable, useful and from a trusted source does well in all three.

The practical consequence is that you do not need three teams or three content calendars. One team that understands the shared foundation, plus a measurement habit for AI answers, covers most of the ground. Splitting the work by acronym tends to produce duplicate pages competing for the same questions.

Where does GEO actually differ?

Three places. First, access: most AI crawlers do not run JavaScript, so content that only appears client-side may rank in Google and still be invisible to ChatGPT or Perplexity. Second, trust signals: 2026 studies summarised by Geoptimizer found earned media made up 84% of links cited by AI engines and that branded web mentions correlated with AI visibility far more strongly than backlinks. Third, measurement: there is no rank to check, so you sample answers to a fixed set of questions and count citations.

There is also a difference in what success looks like. In search, a visitor clicks through and you can see the session. In an AI answer, the reader may get what they need from the summary and never visit, so a mention of your brand in the answer is the win in itself, and some of its value shows up later as branded searches and direct visits.

What should you do first?

Notice that four of the five are also good SEO. The extra GEO work is the measurement loop and the weight you put on earned mentions.

Sequence matters. Access comes first because nothing else counts if crawlers cannot read the page. Answers come next because they are fully in your control. Mentions take longest, so start them early and let them run alongside everything else.

• Fix access: make sure key pages render their content in raw HTML.
• List the questions buyers ask and map one page to each.
• Rewrite those pages answer-first, with specific, sourced facts.
• Earn mentions: reviews, partner pages, communities, press.
• Measure AI share of voice weekly alongside search clicks.

How do the three fit into one content plan?

Plan by question, not by acronym. Start with the questions your buyers ask across the journey, from “what is this problem” to “which provider should I choose”. Assign each question to one page. Write that page so it can rank in search, answer the question in its first lines and stand on its own as a quotable passage. That one page then serves SEO, AEO and GEO at once.

Where the plans do diverge is distribution. SEO rewards links and internal linking; GEO rewards being mentioned on the sites AI engines cite for those questions. Add a distribution step to each important page: who else should be writing about this, and how do you help them do it?

How should you split budget between SEO and GEO?

Most of the budget should go to the shared foundation, because it pays off in every channel: crawlable pages, strong answers to real questions, and a reputation others repeat. Add a small, fixed slice for GEO-specific measurement and for earning mentions on the sources AI engines cite in your category.

Revisit the split each quarter using your own numbers. If AI referral traffic and signups from cited pages grow, move more effort to earning mentions; if search still drives most qualified traffic, keep the emphasis there. Let the data, not the acronym of the month, decide.

Which tactics are overrated?

Files and tags that promise AI visibility. In 2026 matched tests, neither schema markup nor llms.txt showed a measurable citation effect, and Google says it ignores llms.txt. Mass-produced pages are worse than overrated: Google’s scaled content abuse policy targets pages generated mainly to manipulate rankings, and the September 2026 spam update hit templated programmatic pages.

In my own work the gains came from the unglamorous loop: a weekly citation check, fixing the pages behind the gaps and tracking citations through to signups. That took AI-answer citation share from ~8% to ~19% at Imagera AI.