What Is Generative Engine Optimization (GEO)?

Where the term comes from

"Generative engine optimization" isn't a marketing invention — it started as an academic paper. In late 2023 a group of researchers from Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi published "GEO: Generative Engine Optimization," which was later accepted to the KDD 2024 conference. They defined a "generative engine" as a search experience that uses a large language model to gather and summarize information into a single answer, rather than returning a list of ten blue links.

The paper introduced a benchmark called GEO-BENCH and tested several content strategies inside a generative-engine prototype. Their headline result was that certain techniques could improve a source's visibility in the generated answer by up to about 40 percent in their experiments. That's a real finding from a real study — but it's a controlled research setup, not a promise about your ChatGPT ranking, and the authors themselves note that what works varies a lot by domain.

What GEO actually asks you to do

Strip away the jargon and GEO is mostly about being genuinely citable. Answer engines pull from content that is clear, specific, well-structured, and trustworthy enough for a model to quote with confidence. In the GEO paper, the strategies that helped most were things like adding relevant statistics, citing credible sources, and quoting authoritative voices — in other words, making your content more substantive, not more gamed.

This is why a lot of GEO advice sounds suspiciously like good writing. If your page directly answers a real question, backs its claims, and reads as authoritative, a generative engine has something worth citing. If it's thin, generic, or padded, there's nothing for the model to hold onto — and no schema trick or "AI-optimized" rewrite reliably fixes that.

How much is GEO different from SEO?

Less than the hype suggests. Google's own guidance on optimizing for its generative AI features states plainly that, from its perspective, optimizing for AI search is optimizing for the search experience — and is therefore still SEO. Google says its AI features are rooted in its core ranking and quality systems, and it explicitly tells site owners they do not need special files like llms.txt, special schema, content "chunking," or AI-specific rewrites for its features.

That's a useful reality check. GEO overlaps heavily with traditional SEO plus classic credibility signals: crawlable, well-structured pages, genuinely useful non-commodity content, real expertise, and being mentioned around the web. Different engines (ChatGPT, Perplexity, Gemini) source content differently, so tactics vary, and best practices are still emerging and often unproven. Treat anyone selling a guaranteed GEO formula with skepticism.

A sane way to start

You don't need to chase every GEO tactic on day one. Start by finding out whether AI engines currently know your business exists and describe it correctly — many small businesses discover the answer is "not really," or that the model repeats a wrong phone number, outdated hours, or a service you no longer offer.

That's the gap our AI visibility checker is built to surface: it shows you how AI assistants currently talk about your business so you can fix the obvious problems first. From there, the durable moves are the unglamorous ones — accurate, consistent business information everywhere it appears, and pages that answer real customer questions well enough that a model would want to cite them.

Frequently asked questions

Sources

• Aggarwal et al., “GEO: Generative Engine Optimization” (arXiv 2311.09735, KDD 2024)
• Google Search Central — “Optimizing your website for generative AI features on Google Search”
• Search Engine Journal — “Google’s New AI Search Guide Calls AEO And GEO ‘Still SEO’”