AEO vs AIO vs GEO – What’s The Difference?

The main term in the AI optimization world seems to be generative engine optimization (GEO). GEO represents the most written-about and the most proven type of optimization for large language models (LLMs). It’s what we offer for brands seeking visibility, narrative control, and positive sentiment in tools like ChatGPT, AI Mode, and others.

The flood of GEO content and providers opened the space up quickly and to differentiate, some are now using other terms. For the most part, they seem to be the same type of product centered on AI visibility or some level of AI tracking. 

Two examples are AI optimization (AIO) and answer engine optimization (AEO). AIO seems to be catching on more than AEO and GEO holds most of the search share. All three trigger AI Overviews answers.

What is AEO?

Answer engine optimization (AEO) is the process of optimizing web content to appear in AI tools, primarily to get brand-written content into AI answers and also monitor AI results, depending on who you ask.

As an offering, AEO appears to consist of two elements: content strategy and ongoing AI tracking. AEO is similar to GEO in that it’s trying to get brand placements in ChatGPT and the like. 

Though sources vary, it seems that AEO is a narrower strategy targeting content relevance, which is likely more useful for small brands budget-wise.

Additionally, AEO previously referred to optimizing rich snippet elements like Google’s People Also Ask and knowledge graph features and has been synonymous with rich snippet optimization.

What is AIO?

AIO has two potential meanings. For one, AIO refers to AI Overviews, Google’s in-search AI platform. We typically use it that way at Terakeet.

AIO also refers to AI optimization, which is a broader marketing strategy that adds AI platforms and models to the mix. Beyond simply getting AI placements, AIO takes a deeper approach, focusing on how LLMs function and optimizing for sentiment, brand equity, and accuracy. 

AIO also brings AI tools into the strategy, using them to create assets and content. Out of AEO and AIO, this one seems to be closest (even synonymous) to GEO, though there are differences.

How are these terms different from SEO?

Whether you’re talking about GEO, AEO, or AIO, each of these terms are distinct strategies from search engine optimization, or SEO. The difference is that GEO, AEO, and AIO are totally focused on generative AI tools, while SEO focuses on organic search.

Consumer behavior is trending towards AI tool-based research and comparison, which is why optimizing for AI tools is so important. But it’s also important to maintain your SEO strategy. 

The best path is to add an AI-focused strategy like GEO to your existing SEO work. Your SEO and GEO efforts synergize, boosting performance across AI and organic search. This approach fills any gaps your brand might be facing.

Why generative engine optimization (GEO) is the winning term

GEO refers to the entire range of AI-centered optimization — anything that impacts brand visibility, reputation, and sentiment in AI platforms. 

This includes content strategy, building owned assets, internal AI training, reputation management strategy, data science, and beyond.

We believe GEO better reflects the full picture of AI optimization and best explains our diverse approach. 

GEO doesn’t just work to improve AI results, it also analyzes the entire organic space, offers opportunity and sentiment analysis, and helps inform digital marketing efforts across the board with learnings from the AI landscape. 

The result of GEO is a secure reputation, brand presence, as well as citations and inclusion in AI tools. As AI search replaces the traditional organic search customer journey, GEO is a vital brand strategy. Because consumer interest in AI search is quickly growing, brands are losing traffic and opportunities to reach audiences early. GEO turns AI search into a new channel for early-stage trust-building.

Names don’t matter, results do

No matter what you call it, today’s AI-driven digital marketing environment requires brands to be present, prominent, and positively showcased across all popular AI platforms. There are strategies with different names but what ultimately matters is staying visible to, and connected with, your audience.