SEO vs GEO: what actually changed

The rise of AI answer engines didn't kill SEO. It added a second, parallel game with a different win condition. In classic SEO you compete to rank — to place your link high on a results page so a human clicks through. In GEO (Generative Engine Optimization) you compete to be cited — to be the source an AI model quotes or summarizes when it answers a question directly, often without the user visiting anyone's site at all. Same web, same content, two different definitions of winning.

Understanding what actually changed — and what didn't — keeps you from either panicking or ignoring it.

Rank versus citation

The old model is a list. You optimize a page, it earns a position for a query, and the value is the click. Ten blue links, and you fight for the top few.

The answer-engine model is a synthesis. Someone asks a question, and the model composes an answer by pulling from multiple sources, naming some of them. There's no list to climb — there's an answer to be part of. You don't win by being ranked first; you win by being one of the sources the model trusted enough to draw from and attribute. That reframes the goal from "own the top position" to "be citable, and get cited often."

The share-of-voice idea

Because an AI answer blends several sources, GEO introduces a metric that has no clean SEO equivalent: share of voice. Across the questions that matter to your business, how often does the model mention you versus your competitors — and how prominently? If a model answers ten buyer questions in your category and names you in two of them while naming a competitor in eight, you're losing the category in AI answers regardless of where you rank in Google.

That's the concept Sight's GEO visibility scoring is built around. It probes real questions in your space and measures two things: coverage — how often the model mentions your domain at all — and share of voice — your rank-weighted slice of the mentions, where being named first counts for more than being named last. It's the closest thing to a "ranking" that answer engines have, and it's measured across a set of questions rather than one query at a time.

What didn't change

Almost all the fundamentals. AI answer engines still reach your site through the same crawling, still read HTML, still benefit from clean structure, valid markup, fast pages, and content that's actually good. The technical hygiene that makes you rank — indexable pages, readable-without-JavaScript content, sensible structured data — is the same hygiene that makes you citable. If anything, GEO raises the stakes on quality: a model quoting you is a much higher-trust act than a search engine listing you, so vague, hedged, or contradictory content gets skipped rather than cited.

This is why "SEO vs GEO" is a slightly misleading framing. They aren't rivals fighting over the same budget. They're two audiences served by one well-built site — which is exactly why we built a single audit that scores both instead of two disconnected reports. For the fuller definition of the GEO side, our learn guide on what GEO is goes deeper.

The takeaway

What changed: the win condition moved from ranking a link to being cited in an answer, and "how often do models mention me versus my competitors" became a metric worth tracking. What didn't change: the technical foundation, which is shared. Don't treat GEO as a replacement for SEO or as a reason to start over. Treat it as a second scoreboard for the same game — and make sure your one site is built to win on both.