GEO is not SEO with a new acronym

There's a debate that's been running for two years: is it GEO, AI search optimization, or just SEO? One camp insists nothing changed. The other wants to declare SEO dead. Both miss the point.

SEO isn't finished — and it isn't unchanged. Ranking still matters because AI engines ground answers in traditional search. What's stacked on top of that pipeline is new enough that teams who only run the old playbook leave half the opportunity on the table.

AI search is a decision channel, not a traffic channel

Classic Google Search optimizes for pages people will click and stay on. Ten blue links. Rank, earn the click, convert on your funnel.

ChatGPT, AI Overviews, and Gemini aren't trying to send someone somewhere. They're trying to be the answer. Buyers often decide inside the chat without hitting your landing page or seeing the brand system you spent months polishing. That makes mentions and citability first-class work — not a side project for the SEO team.

The ranking pipeline got more steps

Traditional search was roughly: index, then rank. AI search keeps that foundation and adds layers: grounding in web results, training-data familiarity, and citability — being selected as a source after you've already been retrieved.

• Grounding still leans on classic ranking. Falling out of traditional search removes you from the AI layer too.
• Training data shapes who the model already 'knows' before it searches.
• Citability is separate from retrieval. You can rank, get pulled as a candidate, and still never be named.

From websites to brands

Models lean hard on third-party sources — Reddit, YouTube, review sites, Wikipedia — depending on the query. Your official site is often a small slice of the answer. Incorrect claims sitting in competitor content get repeated as confidently as true ones. Off-domain reputation work is now part of the job.

Measurement looks like brand marketing

Performance marketing spoiled us with tagged clicks. AI search removes the click. When the decisive moment happens in chat, first- and last-click models miss it. What's left looks like share of voice: how often, and how favorably, models mention you versus competitors across the prompts that matter.

Demand data is sparse and skewed

Prompt-volume tools rarely come from the AI engines themselves. They're often reconstructed from clickstream harvested via free extensions — not your enterprise buyers. Build prompt sets from your real customer journey instead of chasing inflated volume numbers.

Visibility differs by model

A brand can dominate ChatGPT and disappear in AI Mode. Fanout behavior, training data, and system prompts diverge. Track ChatGPT, Gemini, AI Overviews, and AI Mode as separate surfaces — Anny was built for that split.

So — GEO or SEO?

Call it whatever you want. The foundation is shared; the surface area is not. Manage training presence, citations, brand mentions, and model-by-model gaps — or watch competitors who do.