AI Search
Plain-English definitions of AI search terms - from GEO and AEO to LLMs and query fan-out. The landscape is changing fast; here is what actually matters.
AEO (Answer Engine Optimization)
The practice of structuring content so it appears as direct answers in AI-powered search tools like Google AI Overviews, Perplexity, and ChatGPT. AEO focuses on clear, concise, answer-first writing that AI systems can extract and surface easily.
AI Overviews
Google's AI-generated summaries that appear at the top of search results for many queries. AI Overviews pull from multiple sources to synthesise a direct answer. Appearing in an AI Overview can drive significant brand visibility - even without a first-page ranking.
Answer-First Format (BLUF)
A writing structure where the direct answer to a question is placed at the very beginning of a section, before any supporting explanation. BLUF stands for Bottom Line Up Front. This format is favoured by AI systems that extract answers from content, and by users who want quick answers.
ChatGPT
OpenAI's AI assistant, capable of answering questions by drawing on its training data and, increasingly, real-time web browsing. As more users search via ChatGPT rather than Google, optimising content for LLM discoverability is becoming a meaningful part of modern SEO strategy.
Crawlability (for AI)
Whether AI systems can access and process your website's content. Some AI tools respect robots.txt and may be blocked if your site restricts crawling. Making content accessible to AI crawlers is an emerging consideration alongside traditional search engine crawlability.
E-E-A-T
Experience, Expertise, Authoritativeness, and Trustworthiness - the framework Google uses to evaluate content quality. AI systems tend to favour content that demonstrates genuine expertise and real-world experience, making E-E-A-T signals increasingly important for AI search visibility.
GEO (Generative Engine Optimization)
The practice of optimising content to appear in AI-generated search results. GEO extends traditional SEO by focusing on how AI systems select, synthesise, and attribute information - including structured formatting, factual density, and clear sourcing.
Hallucination
When an AI model generates information that is factually incorrect or fabricated, presented with apparent confidence. Hallucinations are a known limitation of LLMs. Well-sourced, clearly structured content on your website can help AI systems cite accurate information about your business.
LLM (Large Language Model)
An AI model trained on vast amounts of text data to understand and generate human-like language. LLMs power tools like ChatGPT, Gemini, and Claude. They are increasingly being used to answer search queries directly, shifting how users discover information online.
Perplexity
An AI-powered search engine that provides direct, cited answers to queries by searching the web in real time. Perplexity is growing in popularity as an alternative to Google, particularly among technical and research-oriented users.
Query Fan-Out
The process AI search engines use to break a complex user query into multiple sub-questions, search for answers to each, and synthesise a comprehensive response. Content that anticipates and answers related sub-questions is more likely to be surfaced across multiple query variations.
RAG (Retrieval-Augmented Generation)
A technique where an AI retrieves relevant information from external sources before generating a response. Google AI Overviews and Perplexity both use RAG - they search the web, retrieve relevant content, then generate a synthesised answer. Well-structured content is more likely to be retrieved and used.
Structured Data
Code added to a page that explicitly describes its content in a format machines can understand. Structured data (typically Schema.org JSON-LD) helps both search engines and AI systems accurately understand who you are, what you do, and what your content covers.
Zero-Click Search
A search result where the user gets their answer directly on the results page - via AI Overviews, featured snippets, or knowledge panels - without clicking through to any website. Zero-click searches are increasing as AI search matures, making brand visibility in these results an important goal even without a click.
Agentic AI
AI systems that can autonomously plan and execute multi-step tasks - browsing the web, using tools, and taking actions on a user's behalf. As AI agents become more prevalent, they will increasingly research, compare, and recommend products and services without human search queries. Brands optimised for AI discovery today are better positioned for this shift.
Brand Entity
How AI systems 'understand' your business - not just your website, but the full picture assembled from your domain, business listings, social profiles, third-party mentions, and structured data. A strong brand entity means AI systems have consistent, accurate information about who you are, what you do, and where you operate. Entity confusion leads to hallucinations and missed citations.
Citation
When an AI system attributes its answer to a specific source - linking to or naming the website it drew from. Being cited by ChatGPT, Perplexity, or Google AI Overviews is the AI search equivalent of a first-page ranking. Citations are driven by content quality, structured formatting, brand authority, and presence on platforms AI engines trust.
Conversational Search
Search queries written as natural language questions or multi-turn conversations, rather than keywords. As AI search matures, users increasingly ask full questions like 'what is the best Google Ads agency in Perth for a small business'. Content structured around natural questions and direct answers performs better in conversational search contexts.
Grounding
The process of connecting an AI's response to real-world, verifiable information - typically by retrieving live web content before generating an answer. Grounded AI responses are more accurate and up-to-date than ungrounded ones. Google AI Overviews and Perplexity both use grounding, which is why well-structured, factually accurate web content can be cited even by AI systems with a training cutoff in the past.
Knowledge Graph
Google's database of entities - people, places, organisations, and concepts - and the relationships between them. When Google's Knowledge Graph has a strong entity record for your business, it can answer questions about you directly in search results and improve your chances of appearing in AI Overviews. Business listings, schema markup, and consistent NAP data all contribute to your Knowledge Graph presence.
Multimodal AI Search
AI search that processes and understands multiple types of input - text, images, voice, and video - rather than text queries alone. Google Lens and ChatGPT's image analysis are early examples. Multimodal search is expanding what 'discoverability' means: image alt text, video transcripts, and structured product data are all increasingly relevant.
Training Cutoff
The date after which an AI model has no knowledge from its training data. Events, businesses, or content created after the training cutoff are invisible to the model unless it uses RAG (real-time web retrieval). This is why keeping your website content current and web-accessible matters - AI tools that browse the web can surface recent content regardless of their training cutoff.
Entity SEO
Optimising how your business, people, and topics are represented as entities in search and AI systems - beyond just keywords. Entity SEO involves building consistent structured data, maintaining accurate business listings, earning third-party mentions, and ensuring your brand is understood as a distinct, trustworthy entity. Strong entity signals improve both traditional rankings and AI citation rates.
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