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You are at:Home»Marketing»Confused by AI SEO Terminology? Here’s Your Cheat Sheet

Confused by AI SEO Terminology? Here’s Your Cheat Sheet

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Posted By sme-admin on May 21, 2026 Marketing

Can you tell the difference between LLMO and AEO? (Hint: There isn’t any). The relatively new world of AI SEO terminology is stuffed with acronyms, abbreviations and buzzwords that can easily confuse.

But why is it important? Because today’s businesses fighting for visibility must embrace AI SEO to futureproof, engage and convert in an ultra-competitive search environment. Artificial intelligence is no longer just influencing SEO; it is redefining it.

AI-driven algorithms are shaping a new digital landscape where traditional optimisation tactics alone are no longer enough.

Given that AI search traffic could surpass traditional search traffic by 2028, it’s probably time you learned the latest AI SEO terminology before you get left behind.

Debunked: 13 Essential AI SEO Terms You Need to Know

Search engines are powered by advanced machine learning models capable of understanding context, intent and user behaviour at a deeper level than ever before.

And with the increasing adoption of answer engines like Gemini, ChatGPT and Claude, organisations need to begin to shift their ways of thinking and analysing success in search.

To remove any confusion, AI SEO specialists at MRS Digital have compiled the 13 most common AI SEO terms that every business should know.

1. GEO, AI SEO, AEO and LLMO (They All Mean the Same Thing)

Most of the confusion around AI SEO terminology comes from these terms. There are four widely used industry buzzwords that primarily mean the same thing: optimising for answer engines, generative engines and large language models.

While the naming may seem complex, GEO (Generative Engine Optimisation), AEO (Answer Engine Optimisation), and LLMO (Large Language Model Optimisation) are merely different acronyms for the same process.

This technique ultimately aims to ensure brand information can be easily extracted and used by AI systems such as ChatGPT, Gemini and Perplexity.

AI SEO also falls into this category as it points to the fusion between traditional SEO techniques with more specific measurement and focus areas for answer engines – AI + Search Engine Optimisation.

2. Mentions and Citations

Mentions and citations are the new rankings. In AI SEO, a mention is when your brand is mentioned in the body copy of an AI answer. This is not necessarily linking to your brand’s website.

A citation is when your domain is cited as a source in an AI chat. This could be an inline citation, but it could also be a background source.

3. Agentic SEO

Agentic SEO describes an advanced approach that uses AI agents to plan, create and perform SEO tasks in a workflow.

For example, instead of an SEO specialist performing manual keyword research and creating strategies, the agent decides what to do next – it continuously adapts to search trends and user behaviour, making SEO more dynamic, efficient and responsive.

4. AIO Optimisation (AI Overview Optimisation)

Next, AI Overviews are a Google-specific SERP feature designed to give users clear, AI-generated answers to common search queries.

Unlike features such as ‘People Also Ask’, they typically appear at the very top of Google results, delivering instant responses to informational searches.

They work by pulling information from multiple web sources and combining it into a concise summary, complete with links to the original content.

This creates a ‘no-need-to-click’ experience, allowing users to get the information they need without scrolling or visiting individual pages.

5. Search Intent Modelling

Search Intent Modelling uses AI to predict and categorise user intent behind queries.

Instead of focusing solely on keywords, this approach ensures content aligns with what users actually want, whether that’s information, navigation, or a transaction to improve relevance and rankings.

6. LLM (Large Language Model)

LLM is an artificial intelligence system that predicts the next word based on previous context and patterns it learned from training data.

Tools like ChatGPT and Gemini use LLMs to generate answers and summaries, so making your information easy to reuse should be a top priority.

7. Entity-Based SEO

Entity-based SEO focuses on optimising content around recognised entities such as people, places or concepts, rather than just keywords.

AI-driven search engines use entities to understand context, making this approach essential for improving visibility and semantic relevance.

8. Predictive SEO

Predictive SEO uses AI to forecast trends, search behaviour and keyword opportunities before they peak. By acting on these insights early, businesses can create content that ranks ahead of competitors.

9. Zero-Click Optimisation

Zero-click optimisation focuses on structuring content in an optimal way to appear in AI-generated answers, where users get information without clicking through. This enhances brand visibility even when traffic doesn’t directly increase.

10. Share of Voice (SOV)

In this context, this metric shows how visible a brand is compared to its competitors. It measures the share of total brand mentions that belong to your brand across AI-generated conversations over a specific time period.

11. Fan-out Queries

These occur when an AI system breaks down a user prompt into several related, shorter search terms that are used for retrieval and grounding.

To increase citation likelihood, content should address both the core topic plus associated sub-questions AI systems may derive from user prompts.

12. Sentiment

In this context, sentiment is the emotional tone behind content, whether it’s positive, negative, or neutral. Sentiment is a common metric used in AI SEO to understand how your brand is described in AI chats on different topics compared to the competition.

13. Multimodal Search

Search has evolved beyond simple text searches. People now take photos to search or supplement a text query with images.

Therefore, it’s no longer enough to rely solely on written content, and brands need to incorporate optimised visuals, video and voice-friendly formats into their marketing strategy to stay competitive.

Why AI SEO Matters

Having a firm grasp on AI SEO terminology ensures marketers have the knowledge to begin to navigate the complexities of modern search and unlock new growth opportunities.

As Jade Powter, AI SEO Lead at MRS Digital, said: “AI SEO terminology is evolving all the time.

“Whether it’s called GEO, AEO or AI SEO again next week – only time will tell what sticks. The key terminology that is ultimately important to pay attention to here is the new means of measurement.

“Share of voice, sentiment and mentions are metrics and terminology you should 100% become acquainted with. This is because referral traffic and conversion numbers don’t tell the full picture when it comes to AI search – people are engaging with content is new ways.”

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