Why “GEO” is the Wrong Acronym: Optimizing for AI Assistants, Not Generative Engines
The industry loves new acronyms. In 2024, “GEO” (Generative Engine Optimization) became the hot buzzword, based on a November 2023 Princeton research paper. But it misses the point entirely.
I coined Answer Engine Optimization (AEO) in 2018 - five years before that paper arrived. But even that term is now incomplete. Here’s why.
GEO makes the same mistake SEO made for two decades: focusing on the algorithm instead of the human.
With traditional SEO, we learned (eventually) that “optimize for the user, not Google” was the winning strategy. Google’s algorithm rewards content that serves users well. Trying to game the algorithm fails; serving users wins.
GEO repeats this error. It focuses on the generative engine - the AI model producing responses. But that’s backwards thinking.
The AI isn’t the endpoint. The user is.
Don’t take my word for it. Listen to the companies building these tools. Microsoft doesn’t sell a “text generator” - they explicitly market Copilot as “your everyday AI companion”. Google states their vision is for Gemini to be a “universal AI assistant”.
A “generator” produces text based on probability tokens. An “assistant” makes recommendations based on trust. That distinction changes everything about how you optimize.
ChatGPT, Perplexity, Google AI Mode, Claude - these aren’t “generative engines” in isolation. They’re AI Assistants helping humans make decisions, learn, and take action. The AI is the intermediary, not the destination.
That’s why I now use Assistive Engine Optimization (Search Engine Land: Search, Answer, and Assistive Engine Optimization). It captures the reality:
- SEO = Optimize so search engines show your link
- AEO = Optimize so answer engines cite you as THE answer
- Assistive Engine Optimization = Optimize so AI assistants confidently recommend you to the humans they serve
The shift in language matters because it shifts your strategy. When you optimize for a “generative engine,” you think about prompts, tokens, and model architecture. When you optimize for an AI assistant serving a human, you think about trust, clarity, accuracy, and being genuinely helpful.
The Methodology: Educating the Child (aka your untrained salesforce)
To achieve this level of trust, you cannot rely on technical tricks. You must treat these platforms as learners. Algorithms are like children that need to be educated, not adversaries to be tricked. You teach them who you are, what you offer, and who you serve.
This education happens through the Algorithmic Trinity:
- The Knowledge Graph: The brain that understands facts (Identity)
- The Large Language Model: The voice that communicates the answer (Conversation)
- The Search Engine: The index that verifies the information (Corroboration)
As documented in Search Engine Land, this trinity is the “new operating system for search”. If you ignore the Knowledge Graph to chase “generative” keywords, you fail to build the entity trust required for an assistant to recommend you.
The Evidence from Inside Google and Bing
This isn’t theory. Bing’s Fabrice Canel confirmed that “the perfect click” is an official internal term - their goal is sending users directly to the right answer, not generating text for its own sake. AI Mode runs cascading background queries, anticipating what users actually need before they ask. That’s assistant behavior, not generator behavior.
The competition has also intensified dramatically. In traditional search, 10+ results meant 10+ chances per query. In AI conversations, 3-7 citations per turn means 70% fewer opportunities to survive. The fitness criteria? Clarity, Consistency, Corroboration - not budget or volume. You win by being trustworthy to the assistant, not by gaming the generator.
The Bottom Line: The industry is five years behind.
The industry is five years behind. While marketers debate “GEO” based on a 2023 academic paper, the platforms have already moved on to the agentic era.
Your goal is no longer just to rank (SEO) or to simply answer (AEO). It is to be the trusted partner that an AI assistant confidently brings to its human user.
GEO is a subset of what AEO addresses (The Evolving Search Landscape). And both are subsets of the real game: becoming the solution that AI assistants confidently recommend to their users.
The algorithms are children that want to understand. Treat them that way.
Summary of proof sources:
| Claim | Source |
|---|---|
| AEO coined 2018 | Rankmedia/Trustpilot webinar |
| GEO coined November 2023 | Princeton paper via Elliance |
| Copilot = “everyday AI companion” | Microsoft official blog |
| Gemini = “universal AI assistant” | Google official blog |
| “Perfect click” = Bing internal term | Search Engine Land |
| Cascading queries / micro-AEO | Search Engine Land |
| Algorithms as children | Entrepreneur |
| Algorithmic Trinity | Search Engine Land |
| Assistive Engine Optimization | Search Engine Land |
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