AI Visibility Glossary
Essential terms for understanding AI optimization, generative engine optimization (GEO), and answer engine optimization (AEO).
A
- AI Assistant
- Conversational AI tools that answer questions, complete tasks, and provide recommendations. Consumer-facing examples include ChatGPT, Claude, Gemini, Siri, and Alexa. These are the interfaces through which users increasingly discover brands and make decisions.
- AI HallucinationRead more
- When AI models generate false, misleading, or fabricated information presented as fact. Central to understanding why AI visibility and brand accuracy matter—and a key pain point for businesses.
- AI Model
- Software systems trained on large datasets to perform tasks like generating text, answering questions, or making predictions. Examples include ChatGPT, Claude, Gemini, and Perplexity.
- AI Optimization (AIO)Read more
- The practice of optimizing your brand's presence and visibility across AI-powered platforms, including both training-based systems (like ChatGPT) and retrieval-based systems (like Perplexity). AIO encompasses strategies to influence how AI models perceive, understand, and recommend your brand.
- AI VisibilityRead more
- A brand's presence, accuracy, and prominence within AI-generated responses. The central concept of AI optimization—understanding and improving how AI systems perceive and recommend your brand.
- Answer EconomyRead more
- The emerging economic landscape where AI assistants provide direct answers instead of links, fundamentally changing how consumers discover and choose brands. In the answer economy, being recommended by AI is the new competitive advantage.
- Answer Engine Optimization (AEO)
- The practice of optimizing content to appear in direct answer formats, including featured snippets, voice search results, and AI-generated summaries. AEO focuses on providing clear, concise answers to specific questions.
B
- Brand Mention
- An instance where an AI system references your brand by name in its response. Brand mentions can be positive, negative, or neutral, and tracking them is essential for understanding your AI visibility.
- Brand MisinformationRead more
- Inaccurate information about a brand that AI models may surface to users. A core problem that AI visibility strategies aim to prevent and correct.
C
- Citation
- When an AI system explicitly references your content or brand as a source in its response. Citations are particularly important in retrieval-augmented generation (RAG) systems like Perplexity that show their sources.
- Citation GraphRead more
- The network of references and sources that AI models use to validate and attribute information. A key concept for understanding how authority flows in AI systems.
- Corpus
- The body of text and data that AI models learn from during training or retrieve from when generating responses. A corpus can include websites, books, articles, Wikipedia, and other digital content.
D
- Data Markup
- Structured code added to website content that helps AI systems and search engines understand what the information means, not just what it says. See also: Schema.org.
E
- Entity Authority
- The perceived trustworthiness and expertise of a brand or entity as understood by AI systems. Built through consistent, authoritative presence across high-quality sources like Wikipedia, news outlets, and industry publications.
G
- Generative AIRead more
- AI systems that create new content (text, images, code) rather than simply analyzing existing data. The foundational technology reshaping how consumers discover and interact with brands.
- Generative Engine Optimization (GEO)
- The practice of optimizing content and brand presence to be favorably included in AI-generated responses. GEO focuses on influencing the outputs of large language models and generative AI systems.
- Grounding
- The process by which AI systems connect their responses to factual, verifiable information. Well-grounded responses cite sources and reflect accurate real-world information about brands and topics.
K
- Knowledge Graph
- A structured database of entities and their relationships used by search engines and AI systems. Being properly represented in knowledge graphs (like Google's) improves how AI understands your brand.
L
- Large Language Model (LLM)Read more
- The AI systems (ChatGPT, Claude, Gemini) that power conversational AI experiences. Foundational knowledge for anyone entering the AI visibility space.
P
- Prompt Injection
- A technique where malicious inputs attempt to override an AI system's instructions. For brands, this represents a security concern where competitors or bad actors might try to manipulate AI responses about your brand.
R
- Reputation Management
- The practice of monitoring and influencing how a brand is perceived online. In the AI era, this extends beyond reviews and search results to include how AI assistants describe and recommend your brand.
- Retrieval-Augmented Generation (RAG)Read more
- A technique where AI models pull real-time information from external sources to supplement their responses. Critical to understanding how brands can influence AI outputs through optimized, retrievable content.
S
- Schema.org
- A collaborative vocabulary of standardized data markup supported by Google, Microsoft, and other major platforms. Implementing schema.org markup helps AI systems accurately interpret and represent your brand information.
- Search Engine
- Platforms like Google, Bing, and DuckDuckGo that index web content and return ranked results based on queries. Increasingly, search engines are integrating AI-generated summaries alongside traditional results.
- Sentiment Analysis
- The process of determining whether AI-generated mentions of your brand are positive, negative, or neutral. Tracking sentiment helps understand how AI systems perceive and present your brand.
- SEO (Search Engine Optimization)
- The practice of optimizing content to rank higher in traditional search engine results. While SEO focuses on search engine outputs, AI Optimization (AIO) focuses on the sources AI models learn from. See also: AI Visibility.
- Share of Voice (AI)
- The percentage of AI-generated responses in your category that mention your brand compared to competitors. A key metric for measuring AI visibility success.
- Social Media Accounts
- Brand profiles on platforms like LinkedIn, X, Instagram, and YouTube. These serve as verified sources that AI models reference when gathering information about organizations and individuals.
- Source Authority
- The credibility and trustworthiness that AI systems assign to different information sources. High-authority sources (academic papers, major publications, Wikipedia) are more likely to influence AI responses.
T
- Training DataRead more
- The information used to teach AI models during their development. Understanding training data is essential to grasping why certain optimization strategies work.
- Training-Based AI
- AI systems that rely primarily on knowledge encoded during their training process (like ChatGPT without browsing). Influencing these systems requires presence in authoritative sources that are likely included in training data.
Z
- Zero-Click Search
- When users get their answer directly from search results or AI responses without clicking through to a website. AI assistants have accelerated zero-click behavior, making AI visibility increasingly important.
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