In one sentence: Grounding is the step where an AI assistant looks up real sources and writes its answer out of what it finds there, rather than answering only from the general knowledge it absorbed while it was being built.
An assistant can reply two ways. It can produce the most plausible sounding answer from everything it absorbed during training, which is ungrounded: fluent, occasionally wrong, and impossible to check. Or it can go fetch material first, a few web pages, a business listing, a document somebody handed it, and write from that. That is grounded. Same model either way. The difference is whether anything got fetched before it started writing.
Ask which brands of garage door a shop three towns over installs. Ungrounded, the assistant guesses from what garage door shops usually carry and hands you a tidy paragraph. Grounded, it opens that shop's page and tells you what the page says.
Nobody publishes the rule for when a system decides to go looking. The pattern owners can count on is narrower: the more a question turns on a specific place, a specific business, or something that could have changed recently, the less use memory is, and questions about local services are all three at once.
You can often spot the difference without knowing anything technical. When an assistant shows the pages it used, it looked something up.
You have no say over what a model absorbed years ago. You have a great deal of say over what it finds when it goes looking, and that is the whole reason grounding matters to you. The page fetched today reflects the edit you made today. Nothing has to be reindexed first, and nobody has to approve it.
What follows from that is unglamorous. A page has to be reachable, and it has to be easy to lift a sentence out of. Copy that buries the answer inside a paragraph of adjectives is hard to quote. A page that states the service, the towns covered, the hours, and a price range in plain sentences is easy to quote, which is why the plainest page on a topic often wins the mention. Short headings that ask the question a customer would ask, with the answer in the sentence underneath, do most of that work. If you want to see how your own pages read to a machine, our free AIO readiness scanner is a reasonable place to start.
Being grounded lowers the odds of an invented answer. It does not remove them. An assistant can retrieve a directory page that has been wrong about your address for years, or a competitor's page that happens to mention your town, and then repeat that source faithfully. Quoting a wrong source accurately is still a wrong answer about you, which is the case for keeping your own facts current everywhere rather than trusting the fetch to sort it out. The formal name for the retrieve then answer pattern is retrieval-augmented generation, and the links shown under a grounded answer are AI citations.
Which gives you something to do that is not guesswork. Ask an assistant the questions your customers ask, look at which sources it opened, and read those pages the way a stranger would. The wrong ones are usually old listings and profiles you can still go and correct, and correcting them is slower than it sounds and worth more than it looks.
Look for sources. If the assistant lists the pages it used, it went and looked. If it hands you a confident answer with nothing behind it, treat that as memory and check the facts yourself before you assume customers are seeing them right.
No. You do not control when it decides to look something up or which pages it opens. You control whether your page is reachable, current, and plainly worded, and that is what makes it worth opening in the first place.
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