AI search optimization (GEO)

In practice

It matters because part of the buying research that used to happen on Google now happens inside AI answers. Those tools read websites, extract claims, and attribute them; Google documents how its AI features select and link the pages they cite ^[2]. A site with plainly stated capabilities, direct answers to common questions, and original data gets quoted. A vague site gets skipped, and the AI describes your competitors instead.

GEO overlaps with SEO but rewards different things: extractable one-sentence claims, cited sources, published data, and question-and-answer content, rather than keyword placement alone.

The term comes from the academic work that formalized it, which measured visibility gains of up to 40% in AI-generated answers from exactly these tactics (Aggarwal et al., 2023) ^[1].

In practice the work is concrete: state what you do in plain sentences a machine can quote, publish original data worth citing, answer the questions buyers actually ask, and maintain the files AI systems read, like llms.txt, an open format with a published spec ^[3]. Off the site, it means being present in the sources AI tools lean on: directories, reviews, and coverage that mentions your name.

Checking your own visibility takes ten minutes: ask ChatGPT or Perplexity the questions a buyer would ask, like "best [what you do] for [who you serve]," and note whether you're named and which sites get cited. In our experience, most established companies discover they're invisible in those answers. That's not bad news. It's an open field.