AI Glossary
Plain-English Definitions for Every AI Concept You'll Encounter
A
Acceptable Use Policy (AI)
A document that defines how employees may and may not use AI tools in the workplace, covering data handling, approved tools, and prohibited uses.
Read more → Learn in: AI for Corporate Teams →Academic Integrity (AI Era)
The evolving principles and practices for maintaining honest, original academic work in a world where AI can generate essays, solve problems, and complete assignments.
Read more → Learn in: AI for Educators →Agentic AI
AI systems that can autonomously pursue goals, make decisions, use tools, and take multi-step actions with minimal human supervision.
Read more → Learn in: AI Agents & Automation →AI Agents
Software programs that use AI to perceive their environment, make decisions, and take actions to achieve specific goals.
Read more → Learn in: AI Agents & Automation →AI Automation
Using artificial intelligence to perform repetitive tasks, make decisions, and execute workflows without manual intervention.
Read more → Learn in: AI Agents & Automation →AI Bias
Systematic errors in AI outputs that reflect prejudices in training data, algorithm design, or deployment context.
Read more → Learn in: AI Fundamentals →AI Ethics
The study of moral principles and guidelines that should govern the development, deployment, and use of artificial intelligence.
Read more → Learn in: AI Fundamentals →AI for Business
The strategic application of artificial intelligence tools and frameworks to improve business operations, decision-making, and competitive advantage.
Read more → Learn in: AI for Corporate Teams →AI for Parents
Guidance for families on understanding, supervising, and setting healthy boundaries around children's use of artificial intelligence tools.
Read more → Learn in: AI for Parents →AI for Recruitment
Using AI tools to screen candidates, match skills to roles, reduce bias in hiring, and streamline the recruitment pipeline.
Read more → Learn in: AI for HR →AI Governance
The policies, frameworks, and oversight structures that ensure AI is used responsibly, ethically, and in compliance with regulations.
Read more → Learn in: AI for Corporate Teams →AI Hallucinations
When an AI model generates information that sounds plausible but is factually incorrect or entirely fabricated.
Read more → Learn in: AI Fundamentals →AI Image Generation
Using artificial intelligence to create original images, artwork, and photographs from text descriptions or reference images.
Read more → Learn in: AI for Creatives →AI in Education
The application of artificial intelligence tools to teaching, learning, assessment, and educational administration.
Read more → Learn in: AI for Educators →AI in HR
The application of artificial intelligence to human resources functions including recruitment, onboarding, analytics, and workforce planning.
Read more → Learn in: AI for HR →AI Literacy
The ability to understand, use, evaluate, and communicate about artificial intelligence tools and their implications.
Read more → Learn in: AI Fundamentals →AI Maturity Model
A framework that assesses how advanced an organisation's AI capabilities are across strategy, technology, data, people, and governance.
Read more → Learn in: AI for Corporate Teams →AI ROI
The measurement of financial returns and business value generated by investments in artificial intelligence tools and initiatives.
Read more → Learn in: AI for Corporate Teams →AI Safety for Kids
Practical strategies and tools for protecting children from AI-related risks including inappropriate content, data privacy, and over-reliance.
Read more → Learn in: AI for Parents →AI Video Generation
Using AI tools to create, edit, or enhance video content from text prompts, images, or existing footage.
Read more → Learn in: AI for Creatives →AI-Native Organisation
An organisation that has fundamentally redesigned its workflows, decision-making, and culture around AI capabilities rather than just adding AI tools to existing processes.
Read more → Learn in: AI-Native Leadership →Artificial Intelligence (AI)
Computer systems that perform tasks typically requiring human intelligence, such as understanding language, recognising images, and making decisions.
Read more → Learn in: AI Fundamentals →C
Chain-of-Thought Prompting
Asking an AI to reason step by step before giving a final answer, which improves accuracy on complex tasks.
Read more → Learn in: Mastering AI Tools →ChatGPT
OpenAI's conversational AI assistant that can write, analyse, code, and reason across a wide range of tasks.
Read more → Learn in: Mastering AI Tools →Claude (Anthropic)
Anthropic's AI assistant designed for safety and helpfulness, known for nuanced reasoning and long-context handling.
Read more → Learn in: Mastering AI Tools →Context Window
The maximum amount of text a language model can process in a single conversation, measured in tokens.
Read more → Learn in: AI Fundamentals →Cursor
An AI-powered code editor that lets you build software by describing what you want in natural language.
Read more → Learn in: Vibe Coding →Custom Instructions
Persistent settings that tell an AI tool about your preferences, role, and desired output format across all conversations.
Read more → Learn in: AI Productivity →D
Deep Learning
A type of machine learning that uses layered neural networks to process complex patterns in large amounts of data.
Read more → Learn in: AI Fundamentals →E
EDGE Method
A structured implementation framework for deploying AI across an organisation in phased, measurable cycles.
Read more → Learn in: AI-Native Leadership →F
Few-Shot Prompting
Providing an AI model with two or three examples of the desired output before asking it to generate a new one.
Read more → Learn in: Mastering AI Tools →Fine-Tuning
The process of further training a pre-built AI model on a specific dataset to improve its performance on a particular task.
Read more → Learn in: AI Fundamentals →Function Calling (AI)
The ability of an AI model to request the execution of specific tools, APIs, or code based on the conversation context.
Read more → Learn in: AI Agents & Automation →G
Gemini (Google)
Google's multimodal AI that can process and generate text, images, audio, and video across Google's ecosystem.
Read more → Learn in: Mastering AI Tools →Guardrails (AI)
Safety mechanisms that constrain AI systems to operate within defined boundaries and prevent harmful or unintended outputs.
Read more → Learn in: AI Agents & Automation →H
Human-in-the-Loop
A design pattern where AI systems require human review, approval, or intervention at critical decision points.
Read more → Learn in: AI Agents & Automation →I
Inaction Tax
The compounding cost of delaying AI adoption, measured in lost productivity, competitive disadvantage, and missed opportunities.
Read more → Learn in: AI-Native Leadership →L
Large Language Models (LLMs)
AI systems trained on vast amounts of text that can generate, summarise, translate, and reason about human language.
Read more → Learn in: AI Fundamentals →Legacy Tax (AI)
The ongoing cost an organisation pays by maintaining outdated workflows and processes instead of adopting AI-native alternatives.
Read more → Learn in: AI-Native Leadership →Loop Compression
The process of reducing the number of steps, handoffs, and delays in a business workflow by redesigning it around AI capabilities.
Read more → Learn in: AI-Native Leadership →M
Machine Learning
A subset of AI where systems learn patterns from data rather than being explicitly programmed with rules.
Read more → Learn in: AI Fundamentals →Make (Integromat)
A visual automation platform for building complex, multi-step workflows between applications and APIs.
Read more → Learn in: Mastering AI Tools →Midjourney
An AI image generation tool that creates high-quality artwork and photographs from text descriptions.
Read more → Learn in: AI for Creatives →Multi-Agent Systems
Architectures where multiple specialised AI agents work together, each handling different aspects of a complex task.
Read more → Learn in: AI Agents & Automation →N
n8n
An open-source workflow automation tool that gives you full control over your data and self-hosting options.
Read more → Learn in: AI Agents & Automation →Neural Networks
Computing systems inspired by the human brain, made up of interconnected nodes that process information in layers.
Read more → Learn in: AI Fundamentals →No-Code Automation
Building automated workflows using visual, drag-and-drop tools without writing any programming code.
Read more → Learn in: AI Agents & Automation →O
Open-Source AI Models
AI models whose code and weights are publicly available for anyone to use, modify, and distribute.
Read more → Learn in: AI Fundamentals →Organisational Fork
The strategic decision point where an organisation either commits to becoming AI-native or continues patching AI tools onto legacy processes.
Read more → Learn in: AI-Native Leadership →P
People Analytics
Using data and AI to analyse workforce patterns, predict retention, measure engagement, and inform talent decisions.
Read more → Learn in: AI for HR →Prompt Engineering
The skill of writing clear, structured instructions to get useful and accurate outputs from AI tools.
Read more → Learn in: Mastering AI Tools →R
RAG (Retrieval-Augmented Generation)
A technique that gives AI models access to external documents or databases so they can answer questions using specific, up-to-date information.
Read more → Learn in: AI Agents & Automation →Runway
An AI-powered creative suite for video editing, generation, and visual effects used in professional production.
Read more → Learn in: AI for Creatives →S
Second Brain (AI)
A personal knowledge management system augmented by AI that captures, organises, and surfaces your notes and ideas.
Read more → Learn in: AI Productivity →Sentiment Analysis
Using AI to identify and categorise the emotional tone of text — whether it's positive, negative, or neutral.
Read more → Learn in: AI for HR →Suno
An AI music generation platform that creates original songs with vocals, instruments, and lyrics from text prompts.
Read more → Learn in: AI for Creatives →T
Temperature (AI Parameter)
A setting that controls how creative or predictable an AI model's responses are, from focused to random.
Read more → Learn in: AI Fundamentals →The Five Frictions
A diagnostic framework identifying the five systemic barriers that prevent organisations from becoming genuinely AI-native.
Read more → Learn in: AI-Native Leadership →Tokens (AI)
The basic units that language models use to process text — typically parts of words, whole words, or punctuation marks.
Read more → Learn in: AI Fundamentals →V
Vector Databases
Specialised databases that store information as mathematical representations, enabling AI systems to find semantically similar content.
Read more → Learn in: AI Agents & Automation →Vibe Coding
Building software applications by describing what you want in natural language and letting AI generate the code.
Read more → Learn in: Vibe Coding →Z
Zapier
A no-code automation platform that connects thousands of apps and services to create automated workflows.
Read more → Learn in: Mastering AI Tools →Zettelkasten (with AI)
A note-taking method based on interconnected atomic notes, enhanced by AI to surface connections and generate insights.
Read more → Learn in: AI Productivity →Zero-Shot Prompting
Giving an AI model a task with no examples, relying entirely on clear instructions and context.
Read more → Learn in: Mastering AI Tools →Try a different search term or category
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