AI terminology can quickly become confusing. Terms like GPT, RAG, tokens, and agents are often used in articles, software demos, and sales presentations without much explanation.
For many people in the food industry, this creates a problem. It becomes difficult to tell the difference between genuine useful technology and unnecessary hype.
The good news is that most AI terms are much simpler than they sound.
Understanding a few key phrases can make it much easier to:
- Understand what tools are actually doing
- Ask better questions when suppliers mention AI
- Spot unrealistic claims
- Use AI tools more confidently and safely
Here are some of the most common AI terms explained in plain English.
AI
AI stands for artificial intelligence. In simple terms, it describes software that can perform tasks that would normally require some level of human thinking or decision-making.
In the food industry, AI might be used to summarise audit reports, draft customer emails, analyse trends in production data, or help organise technical documentation.
The important thing to understand is that AI is a very broad term. It covers many different technologies, from simple automation through to advanced tools like ChatGPT.
GPT
GPT stands for Generative Pre-trained Transformer, which sounds far more complicated than it really is.
The easiest way to think about GPT is as a type of AI system designed to generate text by predicting what words should come next in a sentence.
When you ask ChatGPT to draft a supplier email or create a product description, it is not “thinking” in the human sense. It is predicting what a good response should look like based on patterns it learned during training.
This matters because it explains why AI can sound confident even when it is wrong.
LLM
LLM stands for Large Language Model.
This is the technology behind tools like ChatGPT, Claude, Gemini, and Copilot. A language model is trained on huge amounts of written content so it can recognise patterns in language and respond naturally.
For a food business, an LLM might help summarise a long technical document, rewrite a procedure in simpler language, or create a first draft of an audit response.
An LLM is essentially the “engine” powering many modern AI tools.
Prompt
A prompt is simply the instruction or question you give to an AI tool.
For example:
“Summarise this supplier complaint”
or
“Draft a customer apology email for a delayed delivery”
The quality of the response often depends on how clearly the prompt is written.
This is why people talk about “prompt engineering”. In reality, it usually just means learning how to ask clearer and more detailed questions.
Hallucination
An AI hallucination happens when an AI system generates information that sounds correct but is actually wrong or made up.
For example, an AI tool might invent a food regulation, quote a non-existent source, or provide incorrect allergen guidance while sounding completely confident.
This happens because AI predicts likely answers rather than checking facts like a human would.
In the food industry, this is especially important because decisions around compliance, allergens, and food safety need accurate information.
RAG
RAG stands for Retrieval-Augmented Generation.
Despite the complicated name, the idea is fairly simple. It means the AI searches specific documents or information before generating an answer.
For example, instead of answering from general training data, a RAG system could search:
- Your internal procedures
- Supplier specifications
- Audit documents
- Technical manuals
This helps the AI give answers that are more relevant to your business.
RAG is becoming increasingly important because it allows companies to use AI with their own information rather than relying only on public knowledge.
AI Agent
An AI agent is an AI system designed to carry out tasks with less human involvement.
A normal chatbot responds when you ask a question. An AI agent goes further by taking actions or completing steps automatically.
For example, an AI agent could:
- Read incoming customer complaints
- Categorise them
- Draft responses
- Flag serious issues for review
In the future, AI agents may help automate more routine office and administrative work across the food industry.
Copilot
Copilot is a term used for AI tools designed to assist people while they work.
The idea is that the AI acts like a helper sitting alongside you rather than replacing you completely.
For example, Microsoft 365 Copilot can help draft emails, summarise meetings, analyse spreadsheets, and organise documents inside tools many businesses already use.
The name “copilot” is important because it reflects how AI is usually most effective: supporting people rather than replacing them.
Token
A token is a small piece of text processed by an AI system.
Tokens are not quite the same as words. A sentence is broken into many smaller pieces when processed by AI.
Most AI systems measure usage, limits, and pricing in tokens rather than words.
For everyday users, the main thing to understand is that larger documents, longer conversations, and bigger reports use more tokens and therefore more processing power.
Multimodal
Multimodal AI means an AI system can work with different types of content, not just text.
Modern AI tools can increasingly handle:
- Text
- Images
- Audio
- Video
- Documents
For example, a multimodal AI tool might:
- Read a photo of a damaged product
- Analyse a production chart
- Summarise a PDF audit report
- Transcribe spoken notes from a site visit
This is one of the reasons AI tools are becoming more useful in practical business settings.
Key takeaway
AI terminology can sound intimidating, but most of the concepts are much simpler than they first appear.
In many cases, these terms describe:
- How AI generates responses
- How it searches information
- How it interacts with users
- What kind of content it can work with
Understanding the basics helps remove some of the mystery around AI and makes it easier to judge where these tools are genuinely useful and where caution is needed.