Most marketers are guessing about artificial intelligence (AI) visibility. Daria Ofitserova shows that there is a better way. In this session, she presents the data science workflow she uses to create content that is more likely to be recommended by large language models (LLMs).

The workflow consists of three steps: first, tracking where a brand stands in semantic space; second, conducting a gap analysis against competitors and across topic clusters; and third, using vector embeddings to guide the creation of content that closes those gaps.
Rather than relying on guesswork or a black-box approach, Daria presents a repeatable system grounded in how language models actually process and retrieve brand information.