The first place a buyer hears about your category may no longer be a search results page. It may be a paragraph generated by a model that scanned the web for them, summarized what it found, and named two or three sources in a small grey link at the bottom. If your brand is not one of those sources, you are not in the consideration set — and you will not know it, because the buyer never clicked.

That is the shift Generative Engine Optimization (GEO) is built for. It is not a replacement for search engine optimization (SEO). It is the discipline of getting your brand surfaced inside answers produced by large language models — Google’s AI Overviews, ChatGPT Search, Perplexity, Microsoft Copilot, and the long tail of vertical agents that pull from the web in real time.

If your marketing team is running an SEO program that was designed in 2022, it is optimizing for a search experience that a meaningful share of your buyers no longer use. This piece explains what GEO actually is, what changed in the last two years to make it urgent, what it asks of your content program, and what trade-off you should expect when you build it in.

GEO is not a buzzword — it came out of a real research paper

The phrase Generative Engine Optimization entered the literature in late 2023, in a paper by Pranjal Aggarwal and collaborators at Princeton, Georgia Tech, and the Allen Institute for AI. The paper introduced GEO as a black-box optimization problem: given a generative search engine that synthesizes an answer from retrieved web sources, how do you write a source page so that the engine quotes it, cites it, or otherwise surfaces your brand in the answer?

The researchers tested specific content treatments — adding statistics, citing authoritative sources, using precise language, including direct quotations — across thousands of queries and a range of models. They reported visibility improvements in the range of 30 to 40 percent for the best-performing treatments. The exact numbers will keep moving as models change. The underlying signal will not: generative engines reward content that looks like it was written by someone who knew the answer, not someone hoping to rank for it.

That is the entire premise of GEO. The engine is no longer matching a query to a page. It is reading a set of pages, deciding which sentences and figures are worth synthesizing, and producing an answer in which your brand either appears or does not.

Why this is urgent now, not next year

Three things shifted in 2024 and 2025 that turned GEO from an interesting research topic into a board-level question for marketing leaders.

Google rolled out AI Overviews. The feature launched at I/O in May 2024 — first in the United States, then to more than a hundred countries — and now sits above the organic results for a large share of informational queries. For many of the questions your buyers ask at the top of the funnel, the AI-generated answer is the first thing on the page. The blue links are still there. They are below the fold for searches that used to convert above it.

ChatGPT Search went live in October 2024, with browsing capability available to free users by the end of that year. Perplexity, which framed itself as an “answer engine” from the start, crossed into mainstream awareness in 2024 and continued raising at multi-billion-dollar valuations through 2025. Microsoft kept investing in Copilot, including inside Office and Edge, which means search-style queries now happen inside Word and Excel for a non-trivial share of knowledge workers.

The publisher economy started rewriting itself in response. The New York Times sued OpenAI and Microsoft in December 2023; News Corp signed a licensing deal with OpenAI in 2024; Reddit signed a data licensing deal with Google that turned its threads into one of the most-cited sources inside AI Overviews. Stack Overflow’s traffic decline after ChatGPT, and Chegg’s collapse in share price, are the canary cases — companies whose business depended on being the destination for a question rather than the source for an answer.

For a B2B marketing leader, the question is no longer whether the search experience is changing. It is how much of your category’s buying journey now happens inside an AI-generated answer, and whether your team has any read on whether you show up there.

GEO changes four things about how content earns its keep

The reflex when people first hear about GEO is to ask whether it is “just SEO with new keywords.” It is not, and treating it that way is what is producing the wave of generic AI-era content currently flooding the category.

SEO optimizes a page so that a search engine ranks it. The unit of value is the click. GEO optimizes a page so that a generative engine quotes it, names the brand, or links to it as a source. The unit of value is the citation — whether or not the click follows.

That distinction reshapes four things.

The first is the kind of writing that wins. Generative engines synthesize. They reward content that hands them a quotable sentence: a clear definition, a specific number with a source, a named framework, a direct quotation from someone with a title. Vague paragraphs that worked for keyword density work against you here, because there is nothing in them worth pulling out.

The second is the role of authority signals. Models trained to retrieve from the web are biased toward sources that look credible to other sources — citations, named authors with verifiable expertise, primary research, datasets. The brand-as-publisher playbook that B2B marketers have talked about for a decade is no longer a content marketing nicety. It is the substrate generative engines use to decide who to quote.

The third is structured information. Generative engines lean heavily on content that is structured enough to parse: clean headings, glossary-style definitions, comparison tables with stable column names, FAQ sections where the question and answer are explicit. This is not a return to schema markup theatre. It is a discipline of writing pages that a model can read without guessing.

The fourth, and the one most teams underestimate, is the surface area outside your own site. Reddit, YouTube transcripts, GitHub READMEs, industry forums, and review sites are now first-class inputs to AI-generated answers. If the only place your point of view exists is on your owned domain, you are competing for citation in answers that pull from places your brand has never shown up.

What this looks like in practice — and what you have to stop doing

A serious GEO program inside a marketing team has three layers, and each one has a corresponding thing the team has to stop doing to make room for it.

The first layer is measurement. You cannot manage what you do not see. The tooling matured fast in 2024 and 2025 — Profound, AthenaHQ, Otterly, Peec AI, and a growing set of enterprise platforms now monitor how often your brand appears across AI search engines for a defined set of prompts, which competitors get cited alongside you, and which sources the engines are pulling from. The trade-off: your team will have to deprioritize some of the keyword-rank tracking that has filled monthly reports for years. Both matter; neither team has unlimited reporting bandwidth.

The second layer is content built for citation, not just rank. That means commissioning original research the engine will quote, writing definitions and frameworks that read as authoritative, and naming the people behind the work. The trade-off: it slows down publishing cadence. A program that produced four thin posts a month should produce one piece worth citing — and the team has to be willing to accept that the volume metric will go down before the citation metric goes up.

The third layer is presence on the surfaces the engines actually read. That means investing in places your brand has historically treated as unowned — Reddit threads in your category, podcast transcripts, expert interviews on independent publications, contributions to open data sets. The trade-off: this work is much harder to attribute. It will not show up in last-click reporting, and a CFO who asks “what did this cost and what did it return” will not get a satisfying answer in the first quarter. This is the part of the program that requires a marketing leader to spend political capital, not just budget.

None of this is exotic. It is the same discipline that worked when search engines first started rewarding genuine expertise over keyword-stuffed pages. The difference is the stakes — and the speed at which the discipline is becoming table stakes for being considered in the category at all.

How to know whether your team is behind

A short diagnostic the marketing director on your team can run before the next quarterly planning meeting:

Pick ten questions a buyer in your category would ask at the top of the funnel. Run each one in Google with AI Overviews enabled, in ChatGPT with search on, and in Perplexity. For each, note three things — whether your brand is named, whether your domain is cited, and which competitor brands appear in your place. Score it without grading on a curve.

If you appear in zero or one of the thirty results, you do not have a GEO problem. You have an absence problem, and the answer engines have already decided what your category looks like without you in it. If you appear in five to ten, you have a real foundation and the question is how to compound it. The middle case is the most common, and the most actionable: a starting position, a known gap, and a clear hypothesis about which content investments would close it.

This is not a hypothetical exercise. The reason we run it with new clients is that the result almost always reframes the conversation away from “we need more SEO” and toward “we need to be findable in the answer, not just on the results page.”

The honest version of where this is going

Two things will keep being true. The first is that the SEO playbook still matters. Generative engines retrieve from the open web, and the same signals that made a page rank well — authority, technical health, internal links, structured data, content depth — make it more likely to be pulled into an answer. A team that abandons SEO to chase GEO will find itself worse at both.

The second is that the share of buyer attention spent inside an AI-generated answer, rather than on a results page, will keep growing. Anyone who tells you they know the final ratio is guessing. What we know is the direction, and the direction is enough to act on.

The teams winning right now are not the ones with the most clever GEO tactics. They are the ones whose content was already worth quoting — primary research, distinct points of view, named experts, specific numbers — and who are extending that discipline onto the surfaces the engines now read. The teams falling behind are the ones still producing the “10 ways to improve your X” content that competes for traffic without ever earning a citation.

If you are the marketing leader making this call, the practical first step is small. Run the diagnostic above. Pick one question your category cares about. Commission the piece of work — a study, a definition, a framework, a benchmark — that would make the answer engines cite you on it. Watch what happens over the next two quarters.

That is the work. The acronym is new. The discipline behind it — being the source other people quote — is what good marketing always was.