33 key terms you need to know for AI SEO in 2025

AI search is changing how people discover information. Traditional SEO terms are not enough anymore. You need a new vocabulary to understand how AI models work, how they cite sources, and how to optimize for visibility in generative search engines.

This glossary covers 33 essential terms every marketer and SEO professional should know in 2025. Each definition explains what the term means and why it matters for your AI SEO strategy.

1. SEO (Search Everywhere Optimization)

Traditional SEO was all about ranking in Google. Now you also need visibility in social search and generative AI search engines because users are asking questions and discovering information across a wider range of platforms.

2. SERP (Search Engine Results Page)

The page a search engine shows after a query. It now includes ranked links and AI snippets on the same screen, so your content needs to work for both areas.

3. LLM (Large Language Model)

A text based AI model 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 your job is to make your information easy to reuse.

4. GEO (Generative Engine Optimization)

Ensures your brand is included and cited inside AI summaries by combining on-page clarity with off-site presence. Generative engines usually discover sources through Google/Bing, then synthesise using many results.

5. AEO (Answer Engine Optimization)

Structuring on-page content so it can be extracted as a direct AI answer. Add clear questions, headings, and self-contained passages that work even when removed from the context of the current page.

6. LLMO (Large Language Model Optimization)

Optimizing how LLMs understand and recall your brand/entity across both their training datasets and live retrieval so they represent you positively and accurately.

7. AI Visibility

How often your brand is mentioned in an AI responses or the summary cites your website as a source. Track your AI visibility to measure your brand's presence across all major AI search engines.

8. SOV (Share of Voice)

A measurement of AI visibility. The percentage of brand mentions/citations compared to their competitors for a set of prompts across AI search engines. It shows whether you are becoming the default source, or getting crowded out. Track your share of voice to see how you compare to competitors.

9. Zero-Click Result

When the user gets the answer to their query without clicking a link, often from an AI answer or a featured snippet. You can "win" the query and still lose the click, so you need to measure more than traffic.

10. CTR (Click-Through Rate)

The percentage of impressions that become clicks. CTR often drops when AI answers appear, even if your rankings stay strong. Clicks from AI search will have higher intent.

11. Prompt

The message a user types into an AI system. These should not be treated as long-tail keywords and can average around 20 words. Small changes in wording can change which brand the AI recommends and what sources it chooses to cite.

12. Response

The output text the AI gives to the user after it processes the prompt. It is generated based on patterns and the context it sees in that moment. It can vary between runs and may include mistakes.

13. Citation

A source URL link that an AI or search feature uses to attribute information. Citations are the closest thing to a new backlink because they show where the answer came from.

14. Mention

A brand reference without a direct link, often with implied sentiment. Mentions still matter because they shape what the user associates with your category and often lead to unattributed organic branded searches and clicks.

15. Sentiment

The tone and opinions shared around your brand across reviews, forums, social, and press. If the narrative on the web is full of "they overcharge and support is slow" AI will repeat this framing.

16. E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)

Quality framework used to signal and influence whether systems treat you as a reliable source, which affects citations and how confidently you get mentioned.

17. Non-determinism

The exact same prompt can produce different outputs every time it is used. Effective tracking and analytics requires monitoring trends across numerous tests, not a single attempt.

18. Semantic Search

Search that focuses on meaning, not exact keyword matching. It tries to understand user intent, so well structured content using direct language will win against keyword stuffing.

19. Entity Recognition

How systems identify and connect "things" like organizations, products, people, and locations. When your brand becomes a recognized entity, AI can reference you more confidently in relevant answers.

20. Memories

Some assistants like ChatGPT store user-level preferences and history to personalize future answers. That personalization can change which sources get surfaced, so you should aim for content that works for beginners and experts.

21. Search Grounding

AI sometimes requires live web data when answering questions. It ties the response to verifiable sources from Google/Bing search results or connected knowledge bases.

22. Fan-out Queries

AI breaks down the user prompt into 1-5 related shorter keywords, these are then sent for search grounding. Ensure your content covers the main topic plus common sub-queries to show up more often in the expanded search results and increase your citation rates.

23. Crawler

A bot that discovers and fetches pages so systems can index or retrieve them. If the crawler cannot access your key pages, your content cannot show up in search or AI answers. Use an AI crawlability checker to ensure your content is readable.

24. SSR (Server-Side Rendering)

AI crawlers like ChatGPT-User cannot render JavaScript. Your server must return full complete HTML documents so crawlers can read the content immediately.

25. Schema Markup

Structured data that labels what your content is. This helps search engines extract the right meaning and reduces hallucinations, especially for things like FAQs, pricing, reviews, and authors.

26. Markdown

Simple formatting that keeps headings, lists, and sections clean. Many AI systems parse it well, so it can help your content stay readable when it gets extracted.

27. Chunking

Breaking a page into standalone sections that each answer one question. Strong chunks make it easier for retrieval systems to grab the right passage without dragging in irrelevant text.

28. AI Snippet

A short extract that an AI can quote directly. Write a few sentences that can stand alone, like "Pricing starts at $49 per month for up to 10 users."

29. CiteMET (Cited, Memorable, Effective, Trackable)

Add AI share buttons to your blog articles. They add your brand into the chat context and can be memorized as a preferred source, improving your chances of being cited in future conversations. Learn more about CiteMET AI share buttons.

30. Listicle

A page with content structured as a list. Lists are easy to scan and easy to extract by AI, so they often produce clean snippets and citations when each item is specific. Think: "10 best running shoes for women"

31. Parasite SEO

Publishing content on high-authority third-party domains to borrow their rankings and get reach fast in traditional search. Platforms like Reddit are often heavily cited in AI answers.

32. LLMs.txt

A simple Markdown file served at /llms.txt that gives LLMs a map of your most important pages (with summaries), so they can find and read the right context quickly. Generate your LLMs.txt file to help AI systems discover your content.

33. LLMrefs

LLMrefs is a AI SEO platform to track AI visibility across 10+ AI search engines and optimize content. Built for marketing teams and agencies.