Understanding AI: A Practical Guide for Businesses
Artificial intelligence (AI) is rapidly becoming part of everyday life, both at home and in the workplace. However, its growth has brought with it a surge of new terminology, technologies and legal and regulatory challenges.
In this knowledge series, we aim to demystify AI by breaking down key concepts and highlighting the issues that matter most for businesses.
So much new terminology, what does it all mean?
One of the main barriers to engaging confidently with AI is the complexity of the language used to describe it. In this first article, we break down some of the key definitions to provide a practical foundation for understanding how AI operates.
AI model
The core “engine” behind AI. A trained algorithm that learns patterns from data and uses those patterns to generate outputs, make predictions or perform tasks. For example, a language model can generate text, while an image model can create visuals.
AI Platform
The underlying ecosystem or infrastructure used to build, train, deploy, scale and manage AI applications and models. It provides the tools, frameworks and environments to develop and operate AI solutions.
AI Agent
An autonomous or semi-autonomous software system (often powered by a large language model/ LLM) that can plan tasks, make decisions and carry out actions using AI models and external tools to achieve a defined goal. AI agents can work independently (or with limited human input) to complete multi-step workflows, for example, dealing with customer queries by independently searching internal databases and providing an appropriate response.
Large Language Model (LLM)
A type of AI model trained on large volumes of text data to understand and generate human-like language. LLMs are commonly used for drafting text, summarising large volumes of information and powering conversational AI tools and power Generative AI.
Generative AI / GenAI
A type of AI system (e.g. ChatGPT) that can create new content, including text, images and code, based on patterns learned from the data it has been trained on.
AI Application / App
A ready-to-use, user-facing software application that enables individuals or businesses to interact with AI to achieve a broader objective. It typically sits on top of an AI platform and combines a graphical user interface (GUI) with one or more underlying AI models (e.g. ChatGPT).
AI System
A broader combination or interconnected network of AI models, applications, data and supporting infrastructure working together to perform a function or automate a process. It goes beyond simple task completion by combining multiple tools, databases, and logic to automate an entire workflow or process autonomously.
AI Tool
Typically a focused, standalone feature that requires users to actively prompt them to get an output. They generally act on command and handle isolated tasks (e.g. Grammarly for spell checking). However, the functionality of AI tools is rapidly developing so that some can now handle multiple tasks.
Why is this important?
These distinctions are not just technical, they can have important implications when assessing risk, allocating liability and understanding how emerging AI regulation may apply.
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Disclaimer
This information is intended for general informational purposes only and does not constitute legal advice. We recommend seeking professional advice before taking any action on the information provided. If you would like to discuss your specific circumstances, please feel free to contact us on 0800 2800 421.
