AI Jargon Buster
AI news and the language around it, simplified.
What is Grounding?
Grounding is the process of connecting an AI model to reliable, external sources of information so its answers are based on facts rather than just its internal memory. When an AI is not grounded, it relies on patterns it learned during its initial training, which can lead to made-up information. By grounding the system, you force it to look at specific documents, company databases, or live data feeds before it generates a response. This ensures that the AI provides accurate, verifiable information that is relevant to your specific business needs and current reality.
Why this matters to you
Grounding is essential for professional work because it turns a creative AI into a reliable tool. It prevents the system from guessing or inventing facts, which is critical when dealing with company policies, financial data, or legal documents. By anchoring the AI to your own verified information, you gain confidence that the output is trustworthy and based on the actual data you provide.
How you might hear this
"We need to ensure our customer support bot is properly grounded in our internal product manuals so it does not give customers incorrect troubleshooting advice."
AI Jargon Buster
Search any AI term, explained in plain English.
Type a term below and search. You will be taken straight to the tool.
Related terms
See how your CV performs against the ATS algorithms that screen candidates before a human ever reads your application.
Try the CV Optimiser →How AI job displacement actually works, what it means for your career, and what to do about it. Written by someone who has been in recruitment for 25 years.
When the Ground Shifts →