What it means
A large language model is an AI model trained on very large amounts of text to predict and generate language. It can answer questions, summarise, translate, draft and reason through problems in text, but it produces likely-sounding answers rather than looking up verified facts.
Real-world example
A regional administration uses an LLM to summarise lengthy public consultation responses. The model groups 2,300 submissions into recurring themes and drafts a summary, and policy officers check the summary against a sample of original submissions before it goes to the council.
Why it matters for AI adoption
LLMs are the engine behind most chatbots and AI assistants. Their usefulness depends heavily on how they are deployed: which model, where it runs, what information it receives, and how its outputs are checked. Choosing an LLM is a decision about capability, cost, data protection and vendor dependency, not just quality.
Questions to ask
- Which model are we using, who provides it, and where does it run?
- How do we check that its outputs are accurate for our specific tasks?