AI Terminology Explained in Plain Language

If you've been reading about AI lately, you've probably come across terms like "LLM", "tokens", and "hallucination" and wondered what on earth they mean. You're not alone.

AI is full of jargon that can make it feel more complicated than it needs to be. But if you're a business owner thinking about using AI, you don't need a computer science degree — you just need to understand the basics.

Here's a plain-language guide to the AI terms that matter most.

LLM (Large Language Model)

This is the technology behind tools like ChatGPT, Claude, and Gemini. A Large Language Model is trained on enormous amounts of text data, which allows it to read, understand, and generate human-like language.

Think of it as a very well-read assistant that can write emails, summarise documents, answer questions, and generate ideas — but it doesn't truly "understand" the way a human does. It predicts the most likely next word based on patterns it has learned.

Why it matters: When someone says "we're using an LLM", they mean they're using AI that processes and generates text — the most common type of AI tool in business today.

Token

A token is the unit AI uses to measure how much text it processes. Roughly speaking, one token is about three-quarters of a word. Every time you type a question or the AI generates a response, tokens are consumed.

Most AI tools charge based on token usage — the more you type and generate, the more you pay.

Why it matters: Understanding tokens helps you estimate AI costs. A short email might use a few hundred tokens. Analysing a long report could use tens of thousands.

Hallucination

This is when AI confidently generates information that is completely wrong. It sounds convincing, reads well, and looks professional — but the facts are fabricated.

For example, an AI might cite a legal case that doesn't exist, or generate statistics that were never published. It's not lying on purpose — it's just predicting what sounds right based on patterns, without actually checking the facts.

Why it matters: This is one of the biggest risks of using AI in business. Any AI-generated content — especially anything involving numbers, legal references, or customer-facing communications — must be reviewed by a human before use.

Agents

AI agents are software systems that use AI to pursue goals and complete tasks on your behalf. Unlike a simple chatbot that answers one question at a time, an agent can plan a series of steps and execute them.

For example, an AI agent could research competitors, compile the findings into a report, and email it to you — all from a single instruction.

Why it matters: Agents represent the next wave of AI productivity. They move AI from "answer my question" to "do this task for me".

MCP (Model Context Protocol)

MCP is an open standard that allows AI models to communicate with different software services and apps. Think of it as a universal translator that lets AI tools talk to your CRM, email, accounting software, and other business tools.

Why it matters: MCP is what makes AI integration with your existing tools possible. Instead of switching between apps, AI can pull data from and push actions to the tools you already use.

Other Terms Worth Knowing

• Prompt — The instruction or question you give to an AI tool. Better prompts lead to better results.
• Fine-tuning — Customising an AI model with your own data so it performs better for your specific use case.
• API — Application Programming Interface. The technical bridge that lets different software systems communicate. It's how developers connect AI tools to your business applications.
• RAG (Retrieval-Augmented Generation) — A technique where AI retrieves relevant information from a specific source (like your company documents) before generating a response, making it more accurate and relevant.

You Don't Need to Be an Expert

Understanding these terms doesn't mean you need to become a technical specialist. But knowing the basics helps you ask the right questions, evaluate AI tools more confidently, and have meaningful conversations with consultants or vendors.

AI is becoming part of everyday business — and like any tool, it works best when you understand what it can and can't do.