Artificial Intelligence (AI) glossary
Artificial Intelligence (AI) is often discussed using technical language, which can make it harder to engage with. This glossary provides clear, plain-English explanations of common AI terms used across this hub and in the wider Civil Service Learning.
You can use this glossary to:
- look up unfamiliar terms as you work through the guidance or learning
- build confidence when talking about AI
- as a reference resource whenever you need a reminder
No technical background is required to use the glossary. Please note, this list of terms is not exhaustive, and we have added some external links to AI A to Z glossaries at the end of this page.
Term description
AI agents
Small computer programmes that can perform tasks on your behalf.
AI model
A ‘map’ of possible connections between data. For example, in a Large Language Model (LLM), the connections will be between words or units of language. When the model receives input from a prompt, it explores those potential connections to generate the most relevant and plausible output.
Anthropomorphising
The act of attributing human traits, emotions, or intentions to non-human entities. For example, saying an AI “thinks” or “understands”.
Artificial Intelligence (AI)
Technology that makes computers more useful and capable of performing complex tasks on their own.
Alternative definition
The AI Playbook for the UK Government uses the definition of AI adopted by Organisation for Economic Co-operation and Development (OECD) countries:
“An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.”
Bias
In the context of AI, bias refers to systematic errors in an algorithm that lead to unfair or inaccurate outcomes. This often occurs when the data used to train the AI reflects existing human prejudices or is not representative of the population it will affect.
Big Data
Extremely large and complex datasets that cannot be easily managed or analysed with traditional tools.
Chatbots
AI personal assistants that can help with the summarising, searching, and writing of information.
Conversational AI
Technologies, such as chatbots or virtual agents, that users can talk to. They use large volumes of data, machine learning and natural language processing to help imitate human interactions, recognising speech and text inputs, and translating their meanings across various languages
Data
Data is a collection of facts, numbers, words, observations or other useful information. Data can exist in various forms, such as numbers, text, images, or measurement. Not all chatbots are equipped with AI, but modern chatbots increasingly use conversational AI techniques such as natural language processing (NLP) to understand user questions and automate responses to them.
Dataset
A structured collection of individual pieces of data. Typically organised in a table or other structured format, datasets are used to train and test AI models.
Hallucinations
When AI makes up information, also known as ‘fabrications’.
Input
Data given to the AI to create an output
Large Language Models (LLMs)
AI systems that use machine learning to help them process language so that they can mimic the way humans communicate.
Machine Learning
A field of computer science under the umbrella of AI where people teach a computer system how to do something by training it to identify patterns and make predictions based on what it has learned.
Natural Language Processing (NLP)
NLP enables computers and digital devices to recognise, understand and generate text and speech by combining computational linguistics, the rule-based modeling of human language together with statistical modeling, machine learning and deep learning.
Output
The response generated by AI.
Prompt
The question you ask to AI.
More A to Z lists of AI terms
Here are some other useful glossaries and lists of AI terms:
- Aaria – AI Glossary (A to Z)
- AiFA Labs – Glossary of Artificial Intelligence
- BBC – The A-Z of AI: 30 terms you need to understand artificial intelligence
- Boston University – Generative AI Tools for Students
- Expert AI – Glossary of AI Terms
- Google for Developers – Machine Learning Glossary
- Massachusetts Institute of Technology (MIT) Media Lab – AI Glossary / Dictionary
- Oxford University – The A to Z of AI terms
- UK Parliament – Artificial intelligence (AI) glossary
- University of Southampton Artificial Intelligence (AI) A to Z glossary
- Zendesk – Generative AI glossary: Key AI terms for 2026 and beyond