The term “GEO”, short for Generative Engine Optimization, has been circulating more and more in SEO conversations. I’ve written about it before, including early takes on the original study by Aggarwal et al., which (I believe) introduced the term and offered some genuinely helpful insights about visibility in LLM-powered platforms like ChatGPT and Perplexity.
At the time, GEO seemed like a useful framework for thinking about optimization in a new context. But lately, I’ve noticed the term being applied way beyond its original scope. It’s showing up across blog posts, LinkedIn, BlueSky, and Twitter threads as a catchall for anything involving AI-assisted search. And honestly? That’s where I feel it starts to lose clarity.
The original context made sense. These tools are becoming search alternatives, and it’s natural that SEOs and others want to understand how to capture visibility there. The term GEO, in theory, helps label that process. But the more I see it used, the more it feels like it’s trying to define a space that’s broader and more complex than what “generative engine optimization” can accurately describe.
Why “GEO” Falls Short
The problem is that GEO is too narrow. It frames the conversation as if we’re only optimizing for generative systems. These are platforms that produce answers using language models. But that’s not the full picture. Search today is much more messy. It spans across AI-assisted systems like Google’s AI Overviews, which mix retrieval with generation. It includes hybrid search engines like Perplexity that cite real-time sources. It even includes search behavior on platforms like TikTok and Reddit.
Google’s AI Overviews, for example, aren’t purely generative. They pull from training data, Google’s index and knowledge graph and combine it all in a summarized LLM output. Bing Copilot works in a similar way.
Even when using a generative interface, what the user gets is a blend of traditional search infrastructure and new AI features. Calling this entire category “generative engines” oversimplifies what these platforms actually do.
Other Terms Aren’t Quite Right Either
If GEO is too narrow, are other alternatives any better? Terms like “Search Everywhere Optimization”, “LLMO”, “AIO”, or “AI SEO” have popped up too. But they either feel like marketing speak or lack clarity. “Search Everywhere Optimization”, which I’ve honestly used quite a bit, sounds a bit bloated. “AI SEO” is too vague. Are we optimizing with AI or for AI? And GEO, despite its growing popularity, is still just one piece of the broader AI-assisted search experience.
Yes, ‘SEO’ historically meant ‘Google optimization,’ but the core principle—improving visibility wherever queries happen—has always evolved with the platforms. The idea of search optimization has grown to include traditional search engines, generative tools, retrieval systems, recommendation algorithms, and more. It continues to adapt without needing a rebrand. That brings us to my main point.
What We’re Really Doing: Search Optimization
To me, what we’re really doing (and what we’ve always done) is optimizing content for visibility wherever people search. That used to mean Google and Bing. Now it also means Gemini, ChatGPT, Perplexity, TikTok, Reddit, and more. The tools have changed. The interfaces have changed. But the goal? It’s still the same: help people find what they need.
Let’s keep it simple, folks. Search optimization already covers adapting to algorithm shifts—whether for featured snippets, voice search, or now AI-generated and AI-assisted answers. It’s not a static discipline; it continues to change along with the platforms we use. That’s why it’s time to drop the “engine” part altogether.
People don’t care whether the system delivering their result is a search engine, a chatbot, or a discovery feed. If it’s used to find information, it’s part of the search experience.
By simplifying the term to just “search optimization,” we keep the focus on what matters: making content visible, useful, and discoverable across every relevant channel. It’s simple. It’s flexible. And it’s better suited for where search is going next.
Let’s Not Overcomplicate It
Sometimes, the best move isn’t coining a new term. It’s recognizing when the language we’ve already been using still works…especially when we update it to match the moment. Dropping the word “engine” may seem like a small change, but it reflects a much bigger shift: search is no longer tied to a specific kind of interface or platform.
Whether someone’s using a search engine, a chatbot, a discovery feed, or a social app…they’re still searching. Our job is to make sure they can find trustworthy, helpful information wherever that search begins.
We don’t need GEO, LLMO, AIO, or any other name. We need clarity. And search optimization gives us that. It’s broad enough to cover the current search environment. It’s also flexible enough to adapt to what comes next.
That’s still search optimization. And it still matters.