How Often ChatGPT, Gemini and Perplexity Update Their Information

Many brands get a fright when they see how AI describes them: an old price, an office that no longer exists, a service they stopped offering. The usual reaction is to think the model got it wrong. In fact it is doing exactly what it knows how to do, and understanding why is the first step to fixing it.

The key is telling apart two things people confuse: the training cutoff and live search.

Cutoff date and live search

A language model is trained on a huge volume of text collected up to a certain point. That point is the cutoff date. Everything the model "knows from memory" comes from before that date. If your business changed something afterwards, the model does not find out on its own.

Live search is the complement. Some engines can query the web at the moment of the question and pull in current information to complete the answer. Perplexity does it almost always. ChatGPT and Gemini trigger it depending on the query. When they search, they can correct old data. When they do not, they rely on memory alone.

Why it describes you with old data

If AI answers about you without searching, it uses what it learned long ago. And here is the important nuance: the model learned from what the web said about you back then. If during that period some now changed information was everywhere, that old version stays recorded and resurfaces.

It happens a lot with prices, addresses, product names or job titles. Also with brands that renamed or pivoted. The model does not lie on purpose; it repeats the footprint your business left in the past.

How to help it use fresh information

You cannot retrain the model, but you can influence what it finds when it searches and what it will learn in future versions. The idea is to make your current information clear, abundant and easy to quote.

1. Keep your site up to date on the data that changes: prices, services, locations, team. With visible dates when it makes sense.
2. Publish recent content that states your current situation. The more you repeat the correct fact across reliable sources, the likelier it gets picked up.
3. Correct external sources with stale data: directory listings, profiles, old press notes that still rank.
4. Make your statements quotable: specific, verifiable sentences an engine can take as they are.

Check which version of you AI handles

Before correcting it helps to see what outdated fact is still circulating. Ask each engine about your brand and watch whether it mentions something stale and which source it seems to come from. That clue tells you which page or profile to update first.

Doing it once gives a snapshot. Since information moves, it helps to track it over time. Tools such as Bee LLM review daily what ChatGPT, Gemini, Perplexity and Claude say about your brand, which lets you spot an old fact that has resurfaced and cut it off before it spreads. Keeping your digital trail fresh and consistent is, in the end, the best way to get AI to talk about you with correct information.

Keep reading: AI search visibility metrics and KPIs · tools comparison.