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GEO vs AEO vs AIO

A throng of generative AI tools are released almost every day. Almost everyone seems to be grasping at how to incorporate AI into their business model and resumes. But what do we call this new field of optimizing generative AI results for our, and our clients’, benefit? How should we refer to the act of improving the visibility of our brand in ChatGPT and other tools?

In this article I will be diving into the most common acronyms to describe these strategies, their similarities and differences, as well as some key tactics to get started. Brace yourself for acronym overload – let’s get to it!

Similarities between AI strategies

  1. Enhancing visibility:
    • The goal of GEO, AEO & AIO are to improve the discoverability and visibility of content. Similar to SEO, these strategies are used by companies and individuals to make their content more noticeable and enticing for their target audience. At the end of the day, all of these strategies are about driving engagement or the consumption of content in some way.
  2. AI & algorithms:
    • GEO, AEO and AIO all involve sophisticated AI technologies and algorithms. Similar to SEO, there might not be a clear path “perfect optimization” but rather best practices which are known to influence algorithms and their outputs.
  3. User-centric approach:
    • Each strategy focuses on understanding and catering to the needs of people. GEO emphasizes generating relevant content, AIO on optimizing broader AI experiences, and AEO on delivering direct answers.

Differences between AI strategies

  1. User Interaction
    • GEO: the user interaction with GEO is more likely to be indirect, with people interacting with the output generated by AI based on the optimizations
    • AEO: interactions with answer engines are often more precise and direct with optimizations helping ensure your content is used as a source.
    • AIO: these optimizations ensure the overall experience of engaging with AI-drive systems and interfaces is smooth, enjoyable and intuitive.
  2. Content structure & format
    • GEO: focuses on creating and structuring content and AI models can easily process to provide informative an appealing output. This often comes in the form of training data, whether direct or indirect.
    • AEO: involves crafting concise and clear content the directly answers questions and is likely to be used by AI systems. Using specific keywords, bullet points and making content easily scannable are key to success.
    • AIO: often goes beyond just content structure to include optimizing the interaction design and taking context into account.
  3. Application focus
    • GEO: primarily focuses on optimizing content for generative AI models, to produce creative outputs. This can include text, images, and other forms of generated content.
    • AEO: concentrates on optimizing content for search engines that provide direct answers, like Google’s AI Overviews. This is about structuring content to ensure it is picked up and displayed in these answer boxes.
    • AIO: encompasses a broader range of AI-driven interactions like chatbots and voice assistants. AIO involves optimizing how AI interacts with users across various platforms and devices, ensuring that the AI delivers relevant, personalized, and efficient responses.

LLMO and GAIO

In case I haven’t introduced enough acronyms in this article, there’s two more worth mentioning. Search Engine Land has landed on calling it artificial intelligent optimization, or AIO. But some of their articles within this category juggle between acronyms like LLMO (large language model optimization) and GAIO (generative AI optimization).

Summary

I’m sure society will be fine if we don’t solve for this confusing alphabet soup tomorrow. However, it would be beneficial for the MarTech (marketing and technology) industry to established a shared vocabulary around this field. Hopefully this brief overview can provide a helpful comparison between these overlapping terms in the meantime.

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