AI/ML
November 3, 2025
Summary
Search engines and AI systems are moving from matching words to interpreting meaning. At the center of this evolution is entity search, a framework that links people, places, things, and ideas into relationships that machines can understand. For marketers and SEO professionals, this shift redefines visibility, moving success from keyword alignment to semantic clarity.
Key Insights
Entity search focuses on context rather than isolated terms. Modern search and large language models (LLMs) identify entities and the relationships between them. A query such as “best running shoes for flat feet” is not just a collection of words. It represents connected ideas like foot type, shoe category, and brand performance. The result is an output that reflects understanding rather than simple text matching.
This shift has deep implications for SEO. Visibility now depends on helping systems interpret meaning. Tools such as structured data, schema markup, and content hubs strengthen this understanding. For example, a page about pizza becomes more discoverable when it also explains related topics such as dough fermentation, New York style, or restaurant culture. Each connected idea expands the web of meaning around the main subject.
Entity search also powers how LLMs process information. These models use embeddings, or mathematical representations of words and concepts, to measure relationships. When a website uses consistent and well-defined entities, it aligns more closely with how LLMs reason. This alignment increases the likelihood of appearing in AI-assisted searches and summaries.
Another important factor is entity salience, which highlights the concepts that matter most within a piece of content. When a brand consistently emphasizes its key topics, both search engines and AI models interpret that consistency as authority. This strengthens presence not only in traditional rankings but also in AI-generated answers such as Google’s AI Overviews.
The growth of multimodal search adds an additional layer. People now use combinations of text, images, and voice to explore information. Entities serve as the connective framework across these modes, allowing systems to interpret meaning regardless of input type. A tutorial about painting a Warhammer miniature, for example, can use text, visuals, or video while maintaining the same underlying concept.
Takeaway
Entity-based search is reshaping how information is organized and understood. Instead of chasing exact keywords, brands must focus on building meaningful connections between concepts, products, and organizations. Content that clearly defines context, relationships, and expertise will stand out to both search engines and AI systems. The new goal is not to rank for single terms but to construct a network of relevance that communicates authority, intent, and trust.