What Generative Engine Optimization (GEO) Is, and Isn't

GEO shows up in almost every 2026 marketing pitch, usually with no source attached. Vendors argue over whether it's the same thing as AEO, course pages sell it as a brand-new skill, and the two platforms that could settle the argument, Google and Bing, rarely get quoted directly. Here is what the term's original paper proposed, and what Google's and Bing's own documentation currently say it is.

What is generative engine optimization (GEO)?

Generative engine optimization (GEO) is the practice of structuring and strengthening content so generative AI systems, such as ChatGPT, Gemini, and Perplexity, cite it when answering a question. The term began in a 2023 research paper, not a marketing department, and both Google and Bing now describe it as an extension of existing SEO practice rather than a separate discipline.

The paper is GEO: Generative Engine Optimization, submitted to arXiv on 16 November 2023 and last revised on 28 June 2024, and accepted to the KDD 2024 conference. Its authors, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, and Ameet Deshpande, worked out of Princeton, the Allen Institute, Georgia Tech, and IIT Delhi. The paper's own project page describes the goal plainly: generative engines summarize information from multiple sources instead of listing ranked links, so a content creator has little control over when or how their page gets used, and GEO was proposed as a black-box optimization framework to help with that. The authors built GEO-bench to test it: 10,000 queries split into 8,000 for training and 1,000 each for validation and testing, tagged across more than 50 categories. Their headline result, reported in the same paper, is that simple GEO strategies improved visibility by up to 40% in generative engine responses.

None of the vendor explainers currently ranking for this term credit that paper. Coursera's article on the topic, updated 9 December 2025, opens with a click-through statistic instead. Conductor's academy page, last updated 4 November 2025, never names an origin at all.

How it works

GEO works because generative AI answers are built on retrieval, not just text generation, and winning the retrieval step is still mostly an SEO problem. Google's guide to optimizing for generative AI features, with a page stamp of 2026-07-10, explains that its AI Overviews and AI Mode rely on retrieval-augmented generation, meaning the model pulls from Google's existing Search index and core ranking systems before it writes an answer. That guide names AEO and GEO as terms "you may see used" online, and states its position directly: "optimizing for generative AI search is optimizing for the search experience, and thus still SEO." According to Wikipedia's entry on generative engine optimization, 2026 was the first time Google put that line into official documentation rather than a conference answer.

Google also sets a concrete bar for eligibility. A page must be indexed and eligible to be shown in Google Search with a snippet, meeting the same technical requirements as regular Search, with no additional technical requirements layered on top for AI Overviews or AI Mode. Separately, the site must be included in Search generative AI features inside Google Search Console, where the Generative AI performance report lives, for that site to be eligible to display at all, according to Google's ai-optimization-guide.

That same guide spends a section on what it calls mythbusting: things site owners can stop worrying about for Google Search specifically. It lists "LLMS.txt files and other 'special' markup," chunking content into tiny pieces, rewriting content just for AI systems, chasing inauthentic "mentions," and overfocusing on structured data, stating flatly that "Google Search itself doesn't use them."

Bing takes a different position. Its live Webmaster Guidelines name Generative Engine Optimization (GEO) as its own term, defining it as focused on "content eligibility for grounding and reference in AI responses." The same document adds a caveat vendors rarely repeat: "GEO does not guarantee grounding or citations in AI experiences." It also lists "Prompt Injection and AI Manipulation," meaning content added specifically to manipulate the language models behind Bing or Copilot, among the practices that can get a site's visibility suppressed or the site delisted entirely. That's a spam tactic, not a GEO technique, whatever a vendor calls it.

Examples: the same practice, different names

The reason GEO feels confusing is that no two sources use the term the same way. Wikipedia's article states this directly: usage "varies across practitioners, vendors, and publications, with no consensus definition," and lists answer engine optimization (AEO), large language model optimization (LLMO), artificial intelligence optimization (AIO), and AI SEO as other names for roughly the same work.

Forrester's Nikhil Lai, quoted in the same Wikipedia article, took a harder line in 2025: answer engine optimization and its related acronyms are "significantly, but not fundamentally, different from SEO," and advocates for AEO, GEO, AIO, and LLMO "tend to exaggerate SEO and AEO's differences to carve a startup-sized hole in marketers' tech stacks." That's worth keeping in mind the next time a pitch deck treats GEO as a from-scratch discipline.

When to use it (and when not)

Use GEO thinking when you're deciding where to put real effort: non-commodity content, clean technical structure, and clear entity definitions, all of which Google and Bing independently point to as what actually moves citations. Don't use it as a reason to buy a tool or service that promises something Google or Bing's own documentation contradicts.

A few concrete checks, drawn straight from the two platforms' guidelines:

• If a pitch says you need an llms.txt file to rank in Google, Google's own guide says the opposite: Google Search doesn't use llms.txt or similar special markup at all.
• If a pitch promises guaranteed citations in AI answers, Bing's guidelines say plainly that GEO "does not guarantee grounding or citations."
• If a pitch suggests rewriting content specifically to game how an LLM parses it, including techniques aimed at manipulating the model itself, that crosses into what Bing's guidelines name "Prompt Injection and AI Manipulation," a practice that can get a site demoted or delisted, not optimized.
• If a pitch treats GEO as replacing SEO rather than building on it, weigh that against Forrester's Lai, Google's own "still SEO" position, and Conductor's "there isn't one" framing of the GEO-versus-AEO split.

One more pitch worth checking against the source: tools and guides built around llms.txt for ranking purposes. In the interest of disclosure, this post runs on bunny.directory's blog, a startup launch directory, which itself publishes a free llms.txt generator tool alongside its launch listings. That tool is free to use either way, but per Google's own documentation above, generating an llms.txt file is not something that moves a Google ranking.

What's new (as of 2026-10-02)

Google put its "still SEO" position into official documentation for the first time with a guide stamped as last updated 2026-07-10, after reportedly stating the same position verbally at conferences before that.

Bing moved the opposite direction, building out dedicated GEO tooling. In February 2026, Bing Webmaster Tools opened AI Performance in public preview, first-party reporting on Total Citations, Average Cited Pages, grounding queries, page-level citation activity, and visibility trends across Microsoft Copilot and Bing's AI-generated summaries. Microsoft described that launch itself as "an early step toward Generative Engine Optimization (GEO) tooling in Bing Webmaster Tools."

In June 2026, Microsoft expanded that report with four preview capabilities: Intents, which classifies grounding queries into categories such as Informational, Commercial, Navigational, Learn and Solve, Research, Creation, and Local; Topics, which clusters related queries into broader subject areas; Citation Share, which shows what percentage of citations for a given query went to your site versus all cited sources; and Compare, which overlays a prior time period onto current reporting. Founders who want a deeper walkthrough of tools like this can see bunny.directory's AI Search Visibility Checker Guide.

Key takeaways

• The term "generative engine optimization" was coined in a 2023 arXiv paper by Pranjal Aggarwal and co-authors, accepted to KDD 2024, not by a marketing vendor.
• Google's July 2026 documentation states officially, for the first time, that optimizing for generative AI search "is still SEO."
• Bing is the platform that treats GEO as its own named discipline in its official guidelines, while stating in the same document that GEO "does not guarantee grounding or citations."
• Vendors split the terminology every which way: Microsoft Advertising and Jasper each separate GEO from AEO, but define the split in opposite directions, while Conductor and Profound treat the two as the same practice.
• Forrester's Nikhil Lai argues the GEO/AEO/AIO/LLMO distinctions from SEO are real but routinely overstated to sell new tools.

FAQ

Is GEO different from SEO?

Not fundamentally, according to the platforms that would know. Google's own 2026 guide states that optimizing for generative AI search "is still SEO," and Forrester's Nikhil Lai has argued the differences between SEO and terms like GEO are "significantly, but not fundamentally" real. Bing is the exception: it names GEO as a distinct concept in its guidelines, focused specifically on eligibility for grounding and citation in AI responses, while still stating that the SEO fundamentals in the rest of its guidelines support that eligibility.

Is GEO the same thing as AEO?

It depends who you ask, and there is no consensus answer. Conductor says GEO and AEO "deal with the same core concept" and compares the distinction to optimizing for Google versus Bing. Jasper splits them the other way: GEO for getting cited by chat-style LLMs like ChatGPT and Claude, AEO for AI-powered search features like Google's AI Overviews and answer snippets. Microsoft Advertising splits them differently again, using AEO for AI agents and assistants such as Copilot and GEO for generative AI search environments.

Who coined the term GEO?

Pranjal Aggarwal and co-authors, in a paper titled GEO: Generative Engine Optimization, submitted to arXiv on 16 November 2023 and accepted to the KDD 2024 conference. The paper introduced GEO-bench, a 10,000-query benchmark, and reported that simple GEO strategies could improve visibility by up to 40% in generative engine responses.

Does GEO guarantee that an AI system will cite my site?

No. Bing's Webmaster Guidelines state this directly: "GEO does not guarantee grounding or citations in AI experiences," the same way SEO never guaranteed a top Google ranking. Any pitch that promises guaranteed AI citations is making a claim the platform itself says isn't possible.

Do I need an llms.txt file for GEO?

Not for Google. Google's own guide names "LLMS.txt files and other 'special' markup" as something site owners can stop worrying about, stating that "Google Search itself doesn't use them." Neither Google's nor Bing's documentation lists llms.txt as a requirement for GEO.

For the AEO half of this split specifically, bunny.directory's Answer Engine Optimization (AEO) Explained for Founders goes deeper on the practical side.