Yesterday I ran a quick experiment that surprised me. I took 15 keywords my team has been targeting for months and checked how they actually perform in AI search results versus traditional rankings. The gap was bigger than I expected.
Here's what I did: I pulled the keywords from our current SEO campaign, ran them through AI Gravity Checker to see their GEO scores, then manually checked ChatGPT and Perplexity responses for each query. I wanted to see which keywords actually showed up in AI-generated answers.
The results were stark. Out of 15 keywords, only 4 appeared in AI search responses at all. The other 11 — despite ranking on page 1 of Google — were completely invisible to AI engines. This matters because if your content isn't being cited by AI, you're missing a growing chunk of traffic.
> GEO Score: A metric indicating how likely your content is to be cited by AI search engines, based on factors like authority, specificity, and source attribution.
The keywords that did show up had something in common: they were specific, question-based, and backed by clear data. For example, "how much does enterprise CRM implementation cost" appeared in 3 out of 5 AI responses. But "CRM software" — our highest-volume keyword — appeared in zero.
This tracks with what I've seen in the GEO vs SEO comparison I've been building. Traditional SEO rewards volume and competition. GEO rewards specificity and authority. They're not the same game.
I ran the same keywords through a GEO Audit Tool to see what recommendations it surfaced. The tool flagged 8 of my 15 keywords as "low citation probability" — and those were exactly the ones missing from AI responses. That's a useful signal for prioritization.
The practical takeaway: if you're only optimizing for Google rankings, you're optimizing for half the search landscape now. AI search is pulling from different signals, and your keyword strategy needs to account for that. Start by checking which of your target keywords actually appear in AI responses — not just traditional SERPs.