AI Definitions for Business Users
AI Power User Glossary (A–Z)
AI Agent
AI Agent is a type of Artificial Intelligence that is able to understand a user’s needs, solve problems and take the initiative, all with limited human guidance.
AI Copilot
AI Copilot is an AI assistant that helps you work better by suggesting ideas, offering help or even doing tasks. It works with you to help you work smarter.
API (Application Programming Interface)
API acts as a bridge between different systems so they can talk, share data and work together.
Automated Blogging and Social Media
These are AI tools that write and improve content for blogs, websites, social media and more. These can be full posts, marketing emails or promotional campaigns.
Chatbot
A Chatbot is a digital assistant that talks to customers, often in a chat window. They can answer questions, help with simple tasks and provide support 24/7. This saves businesses time and improves customer service.
Data Analysis
Data Analysis quickly assesses huge amounts of information to find patterns, trends and make predictions. This helps businesses make smarter decisions.
Effective Business Intelligence
Effective Business Intelligence is an AI tool that turns complex data into useful insights. It can predict customer behaviour, spot market opportunities and highlight risks. This helps businesses plan better and understand customers.
Embeddings
Embeddings turn words, images or data into numbers which help AI understand meanings and find connections easier. Searches become smarter, chats are more accurate and customer recommendations are more relevant.
Generative AI (GenAI)
GenAI creates content like product ideas, emails, blogs and ads by learning from data it is given. It can personalise customer experiences, speed up content creation and boost marketing results.
GPT (Generative Pre-trained Transformer)
GPT is a type of AI model that can understand and generate natural text in response to human prompts. It can assist with content creation, chatbots and customer support.
Latency
Latency is the time it takes for AI to reply to queries. Low latency = fast response.
LLM (Large Language Model)
A Large Language Model is AI trained on huge amounts of text to understand and create human-like language. It can quickly answer questions, write emails, summarise content and much more.
Model
A Model is an AI system trained to complete specific tasks, like answering customer questions, suggesting products, or automating services.
Multimodal AI
Multimodal AI combines text, images, audio and video to understand information better and make more accurate decisions. It fills in gaps and handles complex situations leading to smarter and more helpful results
MCP (Multi-Channel Processing)
Multi-Channel Processing (MCP) allows AI to manage input and output across multiple communication channels (e.g., text, voice, email, chat) simultaneously. Businesses can provide fast, consistent support across chat, email, voice and social platforms by uniting messages and automating responses in one system.
Business value: Enables seamless customer experience across platforms, boosts efficiency in contact centers, and supports omnichannel engagement strategies.
Recommendation Engine
A Recommendation Engine is an AI system that suggests things (like products or videos) based on what someone has liked, viewed, or bought before.
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is an intelligent and easy way for AI to stay up to date. It accesses the latest information before responding, so answers are always current and accurate.
Sentiment Analysis
Sentiment Analysis can understand the mood or emotion behind text, for example: sentient analysis can decide if a review or comment is happy, angry or neutral. This then shows how customers feel so businesses can fix problems, protect their brand and make better decisions.
Token
A small unit of text (like a word or part of a word) that AI models use to break down and understand language. The number of tokens affects response size and cost.
Vector Embedding
Vector embedding turns words, images or data into numbers, which helps AI quickly find, compare and connect the right information. This makes searches, recommendations and customer support faster and more accurate.
