Glossary
Training Data Cutoff
A training data cutoff is the latest period represented in a model’s pretraining data, though providers may not disclose one precise date and retrieved information can be newer. A cutoff therefore does not tell you whether a specific AI answer used live search.
In plain terms
It is the boundary of what the model learned during training, separate from what it can retrieve now.
Why it matters
Brand facts published after training may still appear through retrieval, while old trained facts can persist when grounding is absent.
How to apply it
- Check whether the answer provides current citations.
- Publish current facts on crawlable pages.
- Do not assume every response uses live search.
Example
A model recalls an old product name from training but gives the current price only after retrieving the vendor’s updated page.
Sources
Related reading
Related terms
Back to the full glossary (75 terms).
Ranking is no longer enough
You need to be cited, mentioned, and recommended.
Being cited, mentioned, and recommended are three different outcomes, and most brands only ever achieve the first one. Ranking is no longer enough because AI engines answer buyers directly and name only a short list of vendors as the recommendation — everyone else is cited in passing, if at all. Get a free AI Visibility Report to see exactly where your brand appears today across ChatGPT, Google AI Overviews, Gemini, Perplexity, and Copilot, where competitors are winning the recommendation instead, and what's keeping you from moving up the shortlist.