Answers / Choosing help

Is GEO just repackaged SEO?

By Hoss · Published July 13, 2026 · Sources linked at the end

The skeptics have a point — take it seriously

When Google published guidance on AI search features, its message was blunt: optimizing for generative AI features on Google Search is still SEO [1]. Plenty of agencies have taken an existing SEO retainer, renamed it "GEO" or "AEO," and doubled the price. If a shop can't tell you specifically what they do that isn't already part of good SEO, you've learned what you needed to know.

The overlap is genuine. AI engines retrieve from search indexes — an unindexed, slow, thin site won't be cited by anything. A business with weak SEO fundamentals should fix those first, and a GEO pitch that skips them is selling the roof before the foundation.

What's genuinely different

1. The measurement surface

SEO measures rankings and clicks. AI visibility is measured by running the questions your buyers actually ask across the engines — repeatedly, because answers are probabilistic — and recording whether you're named, recommended, and cited. There is no rank tracker for this; it's a different instrument. It matters because the engines barely agree: one study of 127,198 citations across five engines found only 2.7% of sources were cited by all five, and seven in ten by just one [2]. "Optimizing for AI" as a single target is optimizing for an average that no engine actually is.

2. Per-engine retrieval mechanics

ChatGPT's search runs on Bing's index and its own crawlers (OAI-SearchBot for search, GPTBot for training — blocking one is not blocking the other). Gemini leans on Google's index and grounding. Perplexity crawls in real time and leans heavily on community sources. Each engine is a separate access checklist — robots.txt tokens, WAF rules, rendering — that classic SEO audits don't cover, because Googlebot getting through says nothing about whether ClaudeBot does.

3. The weight of third-party corroboration

SEO largely rewards what you publish on your own domain. AI recommendation engines lean disproportionately on what others say: one analysis of 150,000+ LLM citations found 40.1% pointed to Reddit and 26.3% to Wikipedia [3]. An AI deciding whether to name your business cross-references reviews, directories, and community threads. If the rest of the internet is silent about you, your own site saying you're great doesn't get you named.

4. The machine-readable layer

Structured data that says what you are (not just that you exist), extractable answers positioned where a retrieval system can lift them cleanly, llms.txt, and — further out — agent interfaces. Some of this brushes against technical SEO; most of it was never in the SEO scope at all.

The questions that expose the difference

You don't need to adjudicate the terminology debate. Ask any vendor — including us — these four questions and the answer sorts itself:

So what should you actually do?

If your SEO fundamentals are weak, fix those first — nothing about AI search changes that order of operations. If you rank well but AI answers never name you, the gap is almost always third-party corroboration or machine access [4], and that's the genuinely new work. Either way, start by measuring: run your buyers' real questions through the engines and see who gets named. That baseline costs almost nothing and turns the vendor conversation from claims into evidence.