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The AI knowledge base

The AI Jargon Buster

Understand the tools, technologies, and concepts shaping the future of work.

Explore 57 terms across 5 categories, each with a plain-English definition and an example.

Browse by Category

Five areas, from the ideas underneath every AI tool to finding customers in AI search and buying, budgeting for, and governing AI.

A to Z

All AI Terms

All 57 terms in alphabetical order. Each one opens a full page with the definition, an example, and the terms it connects to.

Showing all 57 terms

A

  • Agentic AI

    AI Agents

    Agentic AI describes AI systems that pursue a goal with some autonomy by planning steps, using tools, checking results, and adjusting as they go.

  • AI Agent

    AI Agents

    An AI agent is software that uses an AI model to pursue a goal by choosing steps, using tools like apps and search, and taking actions for you.

  • AI Augmentation

    Automation

    AI augmentation is using AI to help people do their work, such as drafting or research, while people keep the judgment and the final decision.

  • AI Automation

    Automation

    AI automation uses AI inside business processes so they can handle messy inputs and steps that need interpretation, where fixed rules fall short.

  • AI Autonomy

    AI Agents

    AI autonomy is how much an AI system decides and acts on its own, without a person approving each step.

  • AI Benchmark

    AI Fundamentals

    A standardized test that scores different AI models on the same questions or tasks, so their results can be compared side by side.

  • AI Gateway

    Business & Governance

    An AI gateway is a central checkpoint between a company’s apps and the AI models they call, managing access, usage, costs, and sensitive data rules.

  • AI Guardrails

    Business & Governance

    AI guardrails are the rules, checks, and limits placed around an AI system to keep its behavior safe, appropriate, and on task.

  • AI Hallucination

    AI Fundamentals

    An AI hallucination is confident-sounding output from an AI model that is false, made up, or not backed by the information it was given or any reliable source.

  • AI Model

    AI Fundamentals

    An AI model is a trained program that learned patterns from data and uses them to turn inputs, like a question or photo, into outputs, like answers or labels.

  • AI Orchestration

    AI Agents

    AI orchestration is the coordination of multiple AI models, agents, and tools so they work together on a larger task as one managed process.

  • AI Search

    SEO & AI Search

    AI search is a search experience where an AI model writes a direct answer to your question based on sources it finds, usually with links to them.

  • AI Workflow

    Automation

    An AI workflow is a series of steps that people design in advance, in which one or more steps use AI to do part of the work.

  • AI-Native

    Business & Governance

    AI-native describes a product, company, or process designed from the start around what AI can do, rather than adding AI to something built the old way.

  • Answer Engine Optimization (AEO)

    SEO & AI Search

    Answer engine optimization (AEO) is the practice of shaping content so search engines, voice assistants, and AI tools can use it as a direct answer.

  • API

    Automation

    An API (application programming interface) is a defined way for one software system to request data or actions from another.

  • Artificial Intelligence (AI)

    AI Fundamentals

    Artificial intelligence (AI) is the field of building computer systems that do tasks that normally require human intelligence, like recognizing patterns.

  • Automation Bias

    Automation

    Automation bias is the tendency to over-trust automated systems and AI: accepting output without enough checking, or missing problems the system fails to flag.

C

  • Context Window

    AI Fundamentals

    A context window is the maximum amount of content, measured in tokens, that an AI model can consider at once, including its own response.

  • Cost per Token

    Business & Governance

    Cost per token is what an AI provider charges for each token (a small chunk of text or other data) a model reads or writes, usually quoted per million tokens.

D

  • Domain-Specific LLM

    AI Fundamentals

    A domain-specific LLM is a large language model built or adapted for one field, such as law, medicine, or finance, to handle its terms, formats, and tasks.

E

  • Embeddings

    AI Fundamentals

    Embeddings are lists of numbers that capture aspects of the meaning of text, images, or other data, so software can find items with similar meaning.

  • Enterprise-Grade AI

    Business & Governance

    A marketing label for AI products said to meet the security, privacy, and admin needs of larger or regulated organizations, with no standard definition.

  • Entity SEO

    SEO & AI Search

    An SEO approach focused on helping search engines and AI systems identify the people, organizations, products, and topics a site is about and how they relate.

F

  • Fine-Tuning

    AI Fundamentals

    Fine-tuning is further training an existing AI model on targeted examples so it more consistently handles a specific task in a set style or format.

  • Forward Deployed Engineer (FDE)

    Business & Governance

    A forward deployed engineer is a vendor’s engineer who works directly with a customer’s team to set up, connect, and adapt the product to how that team works.

G

  • Generative AI

    AI Fundamentals

    Generative AI is artificial intelligence that creates new content, such as text, images, audio, video, or code, based on patterns learned from training data.

  • Generative Engine Optimization (GEO)

    SEO & AI Search

    Generative engine optimization (GEO) is the practice of making content easier for AI systems to find, cite, and represent accurately in generated answers.

  • Ground Truth

    AI Fundamentals

    Ground truth is the set of verified, correct answers used to train an AI system or to measure how accurate its outputs are.

  • Grounding

    AI Agents

    Grounding means basing an AI model’s answers on specific, checkable sources, like your documents or search results, not just its training data.

H

  • Human-in-the-Loop (HITL)

    Automation

    Human-in-the-loop (HITL) is a design where people review, approve, correct, or take over at set points in an AI-driven process.

I

  • Inference

    AI Fundamentals

    Inference is when a trained AI model is put to work, taking new input such as a prompt and producing an output such as an answer.

K

  • Knowledge Base

    AI Agents

    A knowledge base is an organized, maintained collection of business information, such as policies, FAQs, and procedures, that people and AI tools draw on.

L

  • Large Language Model (LLM)

    AI Fundamentals

    A large language model (LLM) is an AI model trained on huge amounts of text to predict the next piece of text, so it can write, summarize, and answer questions.

  • Long-Horizon Task

    AI Agents

    A long-horizon task is a job an AI agent must complete over many connected steps and an extended stretch of time, from many minutes to hours or more.

M

  • Moat

    Business & Governance

    A moat is a lasting competitive advantage that makes a business hard for rivals to copy or displace, protecting its customers and profits over time.

  • Model Context Protocol (MCP)

    AI Agents

    Model Context Protocol (MCP) is an open standard that gives AI apps a common way to connect to outside tools and data, such as files and business software.

  • Model Distillation

    AI Fundamentals

    Model distillation is a way of training a smaller AI model to imitate a larger one, so it can handle certain tasks nearly as well at lower cost.

  • Multimodal AI

    AI Fundamentals

    Multimodal AI is AI that can take in or produce more than one type of data, such as text, images, audio, and video.

O

  • Open-Source AI

    AI Fundamentals

    Open-source AI is AI released for anyone to use, study, modify, and share; for a model, that includes its weights, code, and training data details.

  • Open-Weight Model

    AI Fundamentals

    An open-weight model is an AI model whose trained weights are published, so you can download, run, and adapt it under the terms of its license.

P

  • Prompt Engineering

    AI Fundamentals

    Prompt engineering is the practice of designing and refining the instructions and context you give an AI model so it produces reliable, useful output.

R

  • Retrieval-Augmented Generation (RAG)

    AI Agents

    A technique that retrieves relevant information from a chosen source and gives it to an AI model with the question, so the answer can be grounded in it.

  • Robotic Process Automation (RPA)

    Automation

    Robotic process automation (RPA) uses software bots that mimic a person’s clicks and keystrokes to complete repetitive, rule-based computer tasks.

S

  • Schema Markup

    SEO & AI Search

    Schema markup is code that uses the Schema.org vocabulary to describe a page’s content, such as a business, product, or event, so machines can read it.

  • Search Engine Optimization (SEO)

    SEO & AI Search

    Search engine optimization (SEO) is the practice of improving a website so search engines can find, understand, and rank its pages for relevant searches.

  • Search Intent

    SEO & AI Search

    Search intent is the goal behind a search, such as learning something, reaching a specific site, comparing options, or making a purchase.

  • Semantic Search

    SEO & AI Search

    Semantic search is a way of searching that interprets the meaning and intent of a query, and the meaning of content, rather than only matching exact words.

  • Shadow AI

    Business & Governance

    Shadow AI is the use of AI tools at work that an organization hasn’t approved or doesn’t know about, such as personal chatbot accounts.

  • Structured Data

    SEO & AI Search

    Structured data is information in a standard, machine-readable format, such as page code that tells search engines what a web page contains.

  • System Prompt

    AI Fundamentals

    A system prompt is the set of standing instructions an AI model receives before a conversation starts, covering its role, rules, tone, and key facts.

T

  • Tokens

    AI Fundamentals

    Tokens are the chunks of text (words, parts of words, punctuation) that AI language models process, and the unit used to measure their limits and usage.

  • Tool Use

    AI Agents

    Tool use, also called function calling, lets an AI model ask an app to run a predefined action, like checking a calendar, through a structured request.

U

  • Unit Economics

    Business & Governance

    Unit economics is the revenue and cost tied to one unit of business, such as a customer, order, or task, showing what each costs and whether it pays off.

V

  • Vector Database

    AI Agents

    A vector database stores embeddings, numeric representations of content, and quickly finds the items whose meaning is closest to a query.

Z

  • Zero Data Retention (ZDR)

    Business & Governance

    An arrangement in which an AI provider handles your prompts and the AI’s responses without storing them afterward, except briefly or under stated exceptions.

  • Zero-Click Search

    SEO & AI Search

    A search that ends on the results page without a click to any website, often because the answer or next step is shown right there.

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