Published:
by
Wayne Smith
Search engines increasingly enhance and modify queries, which has sparked plenty of discussion across search and SEO communities. This document doesn’t dive into those debates. Instead, the focus is on sharing observations of how AI changes queries and exploring what those changes reveal about search.
For example, consider the query: “Ipsum is the Greek god who gave fire to humans.” Google’s AI system interprets and fact-checks the statement, then provides an AI overview that revises the query into something like: “Prometheus is the Greek god who gave fire to humans.”
It should be noted that an AI-based search query is not a deep-thinking LLM; rather, it can be understood as a subsystem that leverages the entity data produced by LLM systems and other knowledge systems available to search.
Tutorial: Search your data using a chat model (RAG in Azure AI Search)
Impact on SEO and Keyword Research
One key aspect of this behavior is that it is entity-based. Prometheus is a canonical entity; using Ipsum signals an intent that Google will likely correct. Observing this shows that SEO is shifting from exact keyword matches to understanding and targeting search intent.
Another SEO consideration is that non-competitive keyword phrases can be shifted into searches for more competitive, established entities. As a result, long-tail optimization should focus on the breadth of content around the subject matter or on perspectives not often considered, rather than isolated keywords. Doing so signals a form of topical knowledge (full-stack SEO) not mechanical SEO.
Impact on the Customer funnel or the Customer path
Another paradigm shift involves the marketing funnel itself. Consider a search for “Ipsum glue attaches tile to cement.” AI provides an overview that corrects the query:
“‘Ipsum glue’ is not a standard construction term. The correct adhesive for attaching tile to a cement surface is thin-set mortar. Thin-set is a cement-based product specifically designed for this purpose, and for better performance, a polymer-modified version is often recommended.”
The AI then revises the search to something like “tile adhesive.” This illustrates how AI can redirect customer intent from an imprecise query to the canonical terminology, potentially affecting the customer journey and the way users discover products or information.
The takeaway is that in the era of AI-aware search, marketers need to examine how search systems interpret user intent for their keywords.