Generative Engine Optimization (GEO) is the practice of structuring a brand's presence — its own content, and what third parties say about it — so that AI assistants such as ChatGPT, Gemini, Claude, and Perplexity name, describe accurately, and recommend it when answering a relevant question. It targets the sources these systems retrieve and, over time, learn from — not the ranking algorithm of a search engine.
The term was introduced in a 2023 research paper by researchers at Princeton University, Georgia Tech, and the Allen Institute for AI, who observed that generative answer engines pull from and synthesise web content in ways meaningfully different from how traditional search ranks it — and proposed a set of optimisation strategies specific to that behaviour (Aggarwal et al., 2023).1
What GEO actually optimises for
A traditional search engine returns a ranked list of links; the user decides which to open. A generative engine — ChatGPT with browsing, Google's AI Overviews, Perplexity, Gemini — instead synthesises an answer, typically naming one or two sources or brands directly. There is no page two. If a business is not named in that answer, it is, for practical purposes, invisible to the person asking.
GEO work therefore concentrates on three things a generative engine actually uses when it forms an answer:
- Retrieval-time content — the pages, directories, and structured data a model's web-search or retrieval step can find and quote right now.
- Third-party signal — reviews, forum discussion, press coverage, and directory listings, which models weigh heavily because they are harder to game than a brand's own claims about itself.
- Accuracy — whether the facts a model states about a business (price, location, services) are correct, since a wrong fact stated confidently is arguably worse than no mention at all.
Why it is not simply SEO with a new name
The overlap is real — content that is well-structured and factually authoritative tends to help both disciplines. But the mechanisms differ enough that treating GEO as an SEO rebrand leads to wasted effort. See our companion piece, GEO vs SEO vs AEO, for a full comparison.
| Question | SEO | GEO |
|---|---|---|
| What is being optimised | Position in a ranked list of links | Presence and accuracy inside a synthesised answer |
| Primary signal | Backlinks, keywords, crawlability | Entity clarity, third-party mentions, factual accuracy |
| Unit of success | Ranking position | Share of AI recommendations |
| Competitive field | Millions of indexed pages | A handful of names an engine actually surfaces |
Why it matters now for professional practices
Clinics and law firms are a useful test case because the underlying decisions are high-stakes and infrequent — exactly the kind of question people now put to an AI assistant before they ask a friend for a referral. If a model states an outdated price, a closed location, or the wrong practice area, the prospective client has no way to know the answer is wrong. Correcting that starts with knowing what the model currently says — which is the audit half of GEO work, distinct from the optimisation half.
What GEO is not
- It is not keyword stuffing repurposed for a new algorithm.
- It is not a guarantee of any specific ranking or citation — these systems are probabilistic and change without notice.
- It is not a substitute for having accurate, genuinely useful information about a business publicly available; it is the discipline of making sure that information reaches the systems that now mediate a large share of first impressions.