How AI models decide which businesses to recommend
Updated 2026-10-27
AI models name a business based on two things: what they learned during training, and what they retrieve from the web when they answer. Clear facts on your own site, consistent information across other sources and credible third-party mentions all raise the odds, but no one outside the AI companies knows the exact ranking logic, so beware of anyone claiming to.
Two sources of knowledge
- Training data: what the model absorbed before its cutoff. Slow to change and outside your control.
- Live retrieval: when a model searches the web for an answer, it reads pages it can reach and reuses what it finds. This is where you can act quickly.
What tends to help
- Crawlable pages: AI crawlers allowed, content available as plain HTML.
- Clear entity facts: who you are, what you offer, where, for whom, stated plainly.
- Consistency: the same facts on your site, profiles and directories. Conflicts make models hedge or get things wrong.
- Third-party coverage: reviews, listings, press and community mentions give models independent confirmation.
- Direct answers: pages that answer a question in the first sentences are easy to quote.
What nobody can promise
Rankings inside AI answers are not published and vary by model, wording and time. Treat claims of guaranteed placement with suspicion. The practical approach is to remove obstacles, state the facts clearly and measure what the models say.