The marketer’s guide to LLM search terms: From SEO to AEO

The emergence of generative AI is transforming online search, prompting a shift in marketing strategies from traditional SEO to approaches that cater to AI-powered search engines and large language models (LLMs). As AI search tools, such as Google's AI Overviews, deliver direct answers on search results pages, users often find the information they need without clicking through to websites, leading to a decline in organic traffic for marketers. To thrive in this new landscape, marketers must optimize content for AI understanding, focusing on depth, accuracy, and structured data markup, as well as answering specific questions in a format that AI can easily reference. This entails a shift toward conversational search and Generative Engine Optimization (GEO), where content is crafted to be understood and cited by AI systems. Techniques like Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) highlight the integration of real-time data into AI responses, emphasizing the need for content that is both discoverable and usable. As AI systems increasingly determine brand authority, marketers are encouraged to reevaluate success metrics from immediate conversions to broader industry influence, ensuring their content remains pivotal in an AI-first search environment.