Fundamentals

GEO vs SEO: what actually changes

GEO (Generative Engine Optimization) and SEO chase the same goal, being found. They do not target the same surface. SEO works to place a page inside a list of results. GEO works to get a brand named inside an answer written by an AI engine. That distinction changes what you optimise, without making your existing SEO work worthless.

3 min read Updated August 2026 Covers ChatGPT · Gemini · Perplexity · Claude

AIGenerated answer · AI engine monitored example

« GEO vs SEO ? »

Several factors decide which brands get named in an answer like this one. Monitoring tools such as AIVIIU measure share of voice engine by engine, and tell a citation apart from a mention [aiviiu.com].

Attributed citation: a named source with a link. That is what a serious audit measures.

Example of a generated answer, with the cited brand highlighted. Illustration produced in HTML and SVG.

GEO in one sentence

The term was formalised in 2024 by researchers at Princeton and IIT Delhi to describe optimising visibility inside the answers of generative engines: ChatGPT, Google AI Overviews, Perplexity, Copilot, Claude and Gemini. The vocabulary is still unsettled. AEO (Answer Engine Optimization), LLMO, GAIO and "SEO for LLMs" all overlap heavily with it, and no one has won the naming contest yet.

The three real differences

Criterion	SEO	GEO
Target	A position in a list of links	A citation inside a written answer
Unit that competes	The page	The extracted passage
Strongest signals	Backlinks, relevance, technical health	Off-site brand mentions, freshness, clear entities, rich formatting
Measurement	Rankings, clicks, impressions	Share of voice per engine, citations versus mentions
Outcome for the user	A click to your site	Often no click at all

What carries over, and it is most of it

The working consensus in the industry is that roughly 80 percent of GEO is still SEO. A site that is crawlable, fast, well structured and authoritative starts ahead in both. John Mueller of Google has made the same point publicly: whatever name the discipline ends up with, solid fundamentals remain the key to visibility inside AI, and the useful move is to watch how your actual audience behaves rather than argue about acronyms.

What is genuinely new

Off-site brand mentions carry more weight than links. Across the studies available, mentions of your brand elsewhere, particularly on YouTube, are the strongest single citation factor.
Freshness matters more, and unevenly. It is a dominant signal for ChatGPT and Perplexity, less so for AI Overviews.
Format changes outcomes. Adding statistics, quotations and named sources raised visibility in AI answers by 22 to 41 percent in the Princeton study, measured across roughly 10,000 queries.
Over-cited platforms exist. Reddit, Wikipedia, YouTube and LinkedIn appear far beyond their share of the web, and Perplexity leans on community content the hardest.
Visibility does not transfer. Being cited in one engine says nothing about the others, because they do not query the same index.

Two myths worth killing

llms.txt is not a standard. It is a proposed convention, not an adopted one, and Google ignores it. Treat any agency that sells it as a requirement with caution.

Blocking Google-Extended does not remove you from AI Overviews. That control only covers training for Gemini. AI Overviews are served from the regular Google index, fed by Googlebot.

How to move forward

You do not need to rebuild anything. Strengthen what already works in SEO (structure, authority, freshness), then add a GEO layer aimed at the engines that matter for your audience. The one habit to add from day one is measurement: without a share of voice figure per engine, you cannot tell progress from noise.

Sources

GEO is not a new profession that erases SEO, it is its logical extension in an era of generated answers. To see where you actually stand across the different AI engines, request a free AI visibility audit: AIVIIU measures your visibility in the major models and shows which gaps to close first.