Why each AI engine recommends different brands
Google AI Overviews, ChatGPT, Claude, Gemini, Grok, Perplexity and Copilot can give different answers to the same question. Here is why, and what it means for your business.
Ask the same question in Google, ChatGPT and Perplexity and you will often get three different shortlists. That is not a glitch. Each system builds its answer from different material, and that has real consequences for any business that wants to be recommended.
Two ways an AI system knows about you
Most answer engines combine two things. The first is what the underlying model absorbed during training, a snapshot of the web and other sources from some point in the past. The second is what the system retrieves live when someone asks a question, usually from a search index.
The balance between the two varies by product and by question. A question about current prices or a local service leans heavily on live retrieval. A broad question about a category may lean more on what the model already learned.
Different engines, different sources
The retrieval side is where engines differ most, because they do not all search the same index.
- Google AI Overviews and Gemini draw on Google’s own search index, so classic Google visibility feeds directly into them.
- Copilot is built on Microsoft’s Bing index.
- ChatGPT search uses its own crawler alongside third-party search providers.
- Perplexity runs its own crawling and index.
- Claude can search the web through a third-party search provider.
- Grok leans heavily on posts from X as well as the wider web.
A business that ranks well in Google but is missing from Bing, or is rarely discussed on the sources a particular engine favours, can be strong in one answer and absent from the next.
Why one fix does not carry across
Because the sources differ, so do the signals that matter. Structured data, consistent business details, third-party mentions, reviews, and how clearly your own pages describe what you do all play a part, but not with the same weight everywhere.
That is why we treat AI search engine by engine. A checklist applied evenly across all of them wastes effort on signals that one engine ignores and misses the ones another depends on.
What to do about it
Start by measuring. Ask the questions your buyers ask, in each engine, more than once, and record who gets mentioned and which sources are cited. Then work back from the gaps, one engine at a time, with strong technical SEO underneath it all.
If you want help with that, apply to work with us.