Wat Is Generative Engine Optimization? The 2026 Global Definition

Wat is Generative Engine Optimization? The Direct Answer

Generative Engine Optimization (GEO) is the practice of structuring and publishing content so that AI answer engines such as ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude cite it directly in their synthesized responses.

That definition does not change across borders. A marketer in Amsterdam typing “wat is generative engine optimization” and a marketer in Chicago typing “what is generative engine optimization” are asking the same question, and they deserve the same answer. GEO is not a US-only concept, and its meaning does not shift when the query is phrased in Dutch. The underlying mechanics, how large language models retrieve, evaluate, and cite sources, work the same way regardless of the searcher’s language or location.

This article builds that definition on three pillars:

1. The academic origin of GEO, traced to peer-reviewed research from Princeton, IIT Delhi, and Georgia Tech.
2. The mechanical split between SEO and GEO, explaining why ranking and being cited are different outcomes.
3. Google’s official 2026 stance, which reframes GEO as part of SEO rather than a replacement for it.

It also fills a specific gap. English-language GEO guides rarely address Dutch or Belgian market dynamics, while Dutch-language agency pages rarely cite primary research. This piece aims to do both: provide a sourced, internationally aware definition that remains relevant to readers in the Netherlands and Belgium.

The Academic Origin of GEO: Princeton, IIT Delhi, and Georgia Tech

GEO is not marketing jargon invented by agencies to sell a new service line. The term was coined in a peer-reviewed academic paper titled “GEO: Generative Engine Optimization,” first released as a preprint in 2023 and formally presented at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) in 2024, one of the most respected venues in data science research.

The paper’s authors are:

• Pranjal Aggarwal
• Vishvak Murahari
• Tanmay Rajpurohit
• Ashwin Kalyan
• Karthik Narasimhan
• Ameet Deshpande

Their affiliations span Princeton University, IIT Delhi, and Georgia Tech/the Allen Institute for AI.

This origin matters because almost no Dutch-language source discussing GEO references the paper. Many Dutch agency pages describe GEO as a new trend without acknowledging that it has a documented research foundation, a defined experimental protocol, and published results. That omission creates a credibility gap, and this article corrects it.

Readers who want to verify the claim can find the original preprint on arXiv (paper ID 2311.09735) and the formal publication record in Princeton University’s research database, listed under the KDD 2024 proceedings.

What the Original GEO-Bench Research Actually Found

To test whether content could be deliberately optimized for AI answers, the researchers built GEO-bench, a benchmark of roughly 10,000 queries spread across nine datasets. They then measured how specific changes to source content affected the likelihood that a generative engine would include and cite that content in its response.

The core findings were striking:

• Targeted optimization techniques boosted AI visibility by 22 to 41 percent.
• Specific tactics, namely citing sources, adding quotations, and inserting statistics, produced a 30 to 40 percent relative improvement in visibility.

This is why GEO deserves to be taken seriously. Many traditional SEO “best practices” circulate through anecdote, forum threads, and vendor case studies. GEO, by contrast, began with an empirical, measurable basis. Its core claims were tested against a defined benchmark and reviewed by academic peers before the marketing industry adopted the term.

SEO vs. GEO: The Core Mechanical Difference

The fundamental split is simple to state:

• SEO optimizes for clicks from a ranked list of links.
• GEO optimizes for citations inside a single synthesized AI answer.

That distinction has structural consequences for how content is written. SEO has historically rewarded long-form, comprehensive pages designed to win and hold a ranking position. GEO rewards self-contained, extractable paragraphs: blocks of text clear and complete enough that an AI model can lift them cleanly into a generated response without needing surrounding context.

The difference becomes concrete when the two outcomes are compared side by side:

Dimension	SEO	GEO
Goal	Rank in a list of links	Be cited inside a generated answer
User action	Click through to a website	Read the AI’s synthesized response
Unit of value	The full page	The extractable passage or fact
Content shape	Long-form, comprehensive	Self-contained, clearly structured blocks
Persistence	Rankings can hold for months or years	Citations are ephemeral and refresh often
Primary metric	Position, impressions, clicks	Citation frequency, share of answer

The Princeton paper anticipated this measurement problem. It introduced an impression metric designed to quantify how visible a source is within a generated response, accounting for factors such as how much of the answer draws on that source and where it appears. It was the first serious attempt to measure this new kind of visibility, and it remains a reference point for the analytics tools now emerging around AI search.

A Crowded Vocabulary: GEO, AEO, LLMO, and AIO

Readers researching GEO will quickly encounter a tangle of overlapping terms. Vendors and practitioners use several labels for roughly the same discipline:

• Answer Engine Optimization (AEO)
• Large Language Model Optimization (LLMO)
• Artificial Intelligence Optimization (AIO)
• AI SEO, used generically

There is no industry consensus on a single umbrella term. A Dutch agency might market “GEO,” a US platform might sell “AEO,” and an enterprise consultancy might pitch “LLMO,” all describing similar work.

This fragmentation is part of the reason Google has pushed back on treating GEO as a separate category altogether.

Google’s 2026 Position: GEO Is Not a Separate Discipline

One of the most significant and under-reported developments in this space is Google’s own position. In 2026, Google published an official guide to optimizing for its generative AI search features, and most GEO content still ignores it.

In that guide, Google describes AEO and GEO as terms “you may see used,” but argues that “optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”

This is not Google denying that AI answer visibility requires attention or new tactics. Instead, Google is arguing that those tactics are an extension of SEO fundamentals, not a replacement discipline. Helpful content, clear page structure, crawlability, authoritative sourcing, and strong internal linking remain the foundation. GEO techniques sit on top of that foundation.

Dutch-market practitioners have reached a similar conclusion. One Dutch SEO specialist, quoted in local coverage, explained that GEO does not replace SEO but builds on it, because without a solid technical foundation, no AI model will pick up the content in the first place. Dutch consultant Marije Weterings frames GEO in comparable terms, describing it as the strategic complement to classic SEO in the era of AI-driven search results.

The balanced takeaway for readers is clear: treat GEO as a specialized skill set and vocabulary within SEO strategy, not as a rip-and-replace alternative to existing SEO investment. Businesses that abandon SEO fundamentals to chase AI citations are likely to lose both.

Does GEO Apply the Same Way in the Netherlands and Belgium?

Yes. The mechanics of AI citation behavior are not market-specific. ChatGPT, Gemini, Perplexity, and Google AI Overviews retrieve and synthesize sources the same way whether the query is in English or Dutch. What differs is adoption and competitive awareness, which in the Netherlands and Belgium currently lag behind the US and broader English-language market.

The Dutch agency landscape reflects that early stage. Starting around January 2025, firms such as SmartRanking (based in Groningen) and Youvia began marketing themselves as “the first Dutch agency” to offer GEO services. Multiple agencies claiming to be first is itself a signal: the market is young, fragmented, and still defining itself.

There is also a noticeable quality gap. Dutch-language GEO content from agencies including SmartRanking, Youvia, Maatwerk Online, Mondo Marketing, and Marije Weterings tends to be:

• Thin, often structured as service landing pages rather than educational resources
• Lead-generation focused, designed to capture inquiries rather than explain the discipline
• Unsourced, relying on general statements such as “AI search engines are becoming more important” without supporting data

Missing from most of this content is the depth found in English-language coverage: data on citation decay rates, ROI benchmarks, measurement frameworks such as share of model or brand mention share, and citations to primary research like the KDD 2024 paper.

That gap matters because Dutch and Belgian searchers are already encountering GEO’s effects every day. AI Overviews appear on roughly 43 to 48 percent of sampled Google queries as of 2026, and Google’s AI Mode has passed one billion monthly users. Whether or not local content explains GEO well, the AI-generated answers shaping buyer decisions in the Benelux are already being written, and they are citing someone.

Why GEO Citations Decay Faster Than SEO Rankings

The most underreported mechanical fact about GEO is decay. Once earned, an SEO ranking can persist for months or even years. GEO citations are far more perishable.

Industry data shows that roughly 50 percent of content currently cited in AI answers is less than 13 weeks old. In practical terms, a page that is well optimized and frequently cited today can drop out of AI responses within a single quarter as newer sources replace it.

The strategic implication is significant. Classic SEO has often been treated as a “set it and rank it” project: publish a strong page, build authority, and maintain the position. GEO cannot be treated as a one-off optimization project. Maintaining citation presence requires continuous, fresh content production.

The scale of the opportunity makes that sustained effort worthwhile:

• AI-referred sessions grew 527 percent year over year in the first half of 2025.
• Seer Interactive’s April 2026 analysis of 5.47 million queries, spanning 53 brands and 2.43 billion organic impressions, found that AI Overviews appear most frequently on informational searches.

Context matters, however: AI search still sends substantially less click traffic than traditional search, with click-based comparisons showing a gap of 91 to 96 percent. But the growth trajectory is steep, and informational queries, the kind that introduce buyers to brands, are exactly where AI answers now dominate.

For non-English-first brands, including those in the Netherlands and Belgium, the conclusion follows naturally. Staying cited requires a consistent, multilingual publishing cadence, not a single translated “GEO landing page” published once and forgotten.

The Governance Side of GEO: Why It’s More Than a Tactic

GEO is not only a marketing question. Academic researchers have begun examining what it means when generative engines become the primary intermediaries for accessing information. Their source-selection decisions effectively distribute attention, authority, and revenue across the web.

A 2026 critical survey of GEO research (covering the period from 2023 through 2026) and a separate 2026 position paper on GEO’s underexamined risks both flag concerns about concentration of citation share and disclosure: who gets cited, why, and whether users understand how those choices are made.

These concerns are almost entirely absent from tactical GEO guides, but they reinforce an important point. GEO is a serious discipline with consequences for how information reaches people, not merely a collection of marketing hacks. Brands that approach it with accuracy, transparency, and genuinely useful content are better aligned with where both search engines and researchers are heading.

Conclusion: GEO Is SEO’s Next Chapter, Not a Replacement

The definitive answer is now clear. Generative Engine Optimization is an academically grounded, globally applicable practice for earning citations inside AI-generated answers. It was coined by researchers from Princeton, IIT Delhi, and Georgia Tech in 2023, validated at KDD 2024, and is now recognized by Google itself as an extension of SEO rather than a separate discipline.

The term and its mechanics apply equally whether the search is typed in English or Dutch. “Wat is GEO” and “what is GEO” have the same answer.

The central strategic truth is equally clear. Because AI citations decay quickly, with half of cited content under 13 weeks old, the real competitive requirement is not a one-time optimization project. It is consistent, structured, multilingual publishing over time.

Ready for GEO That Doesn’t Decay? See How KOZEC Keeps You Cited

The decay problem creates a practical challenge for lean marketing teams. If AI citation presence depends on always-on content production rather than sporadic campaigns, a team of one to five marketers cannot realistically keep pace through manual effort alone.

KOZEC (Keyword Optimized Zero Effort Content) was built for exactly this gap. The platform uses agentic AI to handle the full content workflow autonomously, from competitor analysis and topic discovery to structured content creation, internal linking, and automated publishing to WordPress and major CMS platforms. Key capabilities for GEO-focused brands include:

• Multilingual content publishing, supporting non-English-first brands in markets such as the Netherlands and Belgium
• Built-in GEO structuring, designed for citation in Google AI Overviews and chat assistants, not just ranked clicks
• The SCO (Search Compliance Optimization) framework, aligned with Google’s recommended practices: useful content, clear pages, smart internal links, and consistent publishing
• Persistent brand context, keeping tone and guidelines consistent across every piece
• Structured data optimization and performance tracking to refine strategy over time

KOZEC reports illustrative client results including +386 percent AI Overview citation growth and +621 percent keyword visibility increase. These figures reflect outcomes from client businesses and should be read as examples of what is possible rather than guarantees.

As AI answer engines refresh their sources every few weeks, the brands that stay cited will be the ones that never stop publishing. To see how a multilingual, always-on content engine can keep a brand consistently visible in AI-generated answers, book a demo at kozec.ai/schedule-a-demo/.