The emergence of artificial intelligence in search technology is fundamentally transforming digital marketing landscapes. With platforms like ChatGPT, Perplexity, and Google’s AI-enhanced features revolutionizing information discovery, marketing professionals face an unprecedented shift in consumer search patterns that extends well beyond conventional SEO practices.
This transformation has birthed Answer Engine Optimization (AEO), a strategic approach helping businesses achieve prominence in AI-generated search responses. However, navigating this evolution requires mastering an entirely new lexicon. Marketing teams that don’t grasp these emerging concepts face the risk of becoming invisible in tomorrow’s digital ecosystem.
These terms represent far more than industry jargon, they define the strategic steps towards a framework and technical foundations that will shape how brands are discovered, trusted, and engaged with in the era of AI-driven search.
To address this challenge, we’ve developed a comprehensive glossary that demystifies AEO terminology and makes this rapidly evolving field more approachable for marketing professionals. This resource serves both brand strategists and performance marketers, providing essential knowledge to remain competitive in the AI-driven search landscape.
Essential AEO Terminology
AEO (Answer Engine Optimization): Strategic methodologies designed to enhance organizational visibility in AI-driven search outcomes. While sharing similarities with traditional search engine optimization (SEO), AEO involves modifying owned, earned, and additional content specifically to influence AI-powered answer engines rather than conventional search platforms.
Agentic Commerce: Retail transactions facilitated by AI agents representing users’ interests. This concept involves leveraging AI search capabilities for commercial purposes directly within AI platforms. Both ChatGPT and Perplexity have introduced preliminary agentic commerce features.
AI Mode: Google’s comprehensive AI search solution that transforms the entire search interface into an AI-powered experience. This chat-style interface enables users to pose follow-up questions and receive detailed, personalized responses.
AI Overviews: Google’s AI-enhanced summary feature that aggregates information from multiple websites to deliver comprehensive answers to user queries. These summaries typically appear prominently in Google’s search results. Google reports that approximately 1.5 billion users engage with AI Overviews monthly as of May 2025.
AI Search: An innovative internet browsing method utilizing AI assistant technology. Users submit requests to AI assistants like ChatGPT, which then systematically search the web for relevant information. These tools can gather data from multiple sources and prioritize content based on predicted user relevance before presenting consolidated results.
Authority: A critical attribute that AI search systems evaluate when determining which information to present to users. Organizations aim to demonstrate expertise on specific topics by providing comprehensive evidence and external validation for claims made in their digital content and communications.
Citation: The source attribution accompanying information in AI search results, displayed as viewable and clickable references. A significant portion of AEO strategy focuses on citation-level optimization, where organizations attempt to influence the primary sources that AI search tools reference. Without this influence, organizations have minimal control over the information AI systems present about them.
Conversational Search Optimization (CSO): A refinement of SEO/AEO strategy focusing on optimizing for dialogue-based queries rather than keyword strings. It accounts for multi-turn interactions and natural language phrasing typical in AI-driven search environments.
Crawler: Within AI search contexts, this refers to large language models (LLMs) that systematically examine websites (“crawling”) to gather information based on user requests.
GEO: Generative Engine Optimization—an alternative term for AEO. Additional synonymous terms include AI SEO and LLMO (Large Language Model Optimization).
Licensing Deal: Agreements between AI search platform providers and content creators that authorize AI model training on proprietary data, typically involving financial compensation. Major news organizations have established such partnerships, including The New York Times with Amazon and News Corp with OpenAI. Social media platforms have similarly opened their data through licensing agreements, such as Reddit’s partnership with OpenAI.
llms.txt: A metadata file outlining a website’s complete structure, essentially providing AI search engines with a comprehensive directory for locating specific information types, such as products, blog content, or case studies. Organizations are increasingly implementing these files as LLM-optimized resources on their websites.
Merchant Program: Initiatives launched by AI search providers to integrate brands more closely into their platform experiences. Current programs primarily focus on enabling brands to provide real-time product feed updates, ensuring users receive the most current information. OpenAI and Microsoft introduced their merchant programs in April, following Perplexity’s November launch.
Multimodal Search: The expanding capability of AI search platforms to process and generate diverse media formats (text, images, video, audio) when conducting user searches. This development requires brands to optimize not only textual content but also video, podcast, and visual materials distributed across the internet.
Schema Markup: Structured metadata that categorizes content types, tagged to help crawlers understand content nature and relevance. Originally an SEO technique, marketing organizations now repurpose schema markup specifically for LLM-focused crawlers.
Synthetic Content Detection: The growing challenge of distinguishing between human-authored and AI-generated material in AI search contexts. Some platforms are starting to implement detection methods to assess trustworthiness and originality, affecting authority and citation.
Vector Indexing: An advanced method for organizing and retrieving content in AI search, where semantic meaning is prioritized over traditional keywords. Websites now begin structuring data for vector-based retrieval models, which impacts their LLM visibility.
Visibility: The extent to which an organization appears in AI-powered search results. For instance, when users ask Perplexity about “leading soda brands,” those mentioned achieve high visibility, while excluded brands demonstrate low visibility. Organizations pursue enhanced visibility through strategic AEO implementation.
Zero-Click Commerce: Online purchasing experiences that eliminate the need for users to click external links. AI search tools handle navigation on users’ behalf, presenting relevant information within their platforms. Some platforms now enable complete checkout processes internally, removing the necessity for users to visit external websites.
Whats next?
As AI search technology continues evolving, marketing professionals must adapt their strategies to remain relevant in this new landscape. Understanding these fundamental concepts provides the foundation for developing effective AEO strategies that ensure brand visibility in an AI-dominated search environment.
The terminology outlined here represents just the beginning of a larger transformation in digital marketing. As AI capabilities expand and new features emerge, this vocabulary will undoubtedly grow and evolve, requiring ongoing education and adaptation from marketing teams worldwide.