AI Agent
Software that takes a goal and carries out multi-step tasks on its own, looking things up, deciding, and acting, instead of answering a single question.
Resource
The Plain-English AI Glossary
The AI terms that actually matter for running a business: defined without the hype, the jargon, or the computer-science detour.
Quick Answer
This is a plain-English AI glossary for business owners: every term explained in a sentence or two, no jargon for its own sake. It covers the concepts that actually affect your business: agentic AI, AI agents and coworkers, automation, prompts, RAG, guardrails, MCP, and more. If a term matters to your business, it should be explainable plainly, that's the whole point.
A to Z
AI Terms, Defined for Business
Automation
Letting software handle a repeatable task end to end, a follow-up email, a data entry, a report, so a person doesn't have to.
Chatbot
A conversational assistant on your website or phone line that answers questions, captures leads, and routes people to the right place.
Generative AI
AI that creates new content, text, images, audio, code, rather than just sorting or scoring existing data.
Large Language Model (LLM)
The engine behind tools like ChatGPT and Claude: a model trained on huge amounts of text that can read and write in plain language.
Prompt
The instruction you give an AI. The clearer and more specific the prompt, the better and more reliable the result.
Prompt Engineering
The skill of writing prompts and instructions that get consistent, accurate, on-brand results from an AI tool.
Hallucination
When an AI states something false with confidence. The reason human review and guardrails matter before AI output reaches customers.
RAG (Retrieval-Augmented Generation)
A technique that lets an AI answer from your own documents and data instead of guessing: grounding replies in real, current facts.
Guardrails
The rules and limits placed around an AI so it stays on-topic, on-brand, and out of trouble, like never quoting a price it shouldn't.
Human-in-the-Loop
A workflow where a person reviews or approves AI output before it goes live. The model drafts; a human decides.
Workflow Automation
Connecting steps across your tools so work flows automatically: a new lead triggers a follow-up, a booking updates the calendar, and so on.
Machine Learning
A type of AI that improves by learning patterns from data, rather than following rules a person wrote by hand.
Natural Language Processing (NLP)
The branch of AI focused on understanding human language, what lets software read an email or understand a spoken question.
API
A connector that lets two pieces of software talk to each other. It's how your site, your AI, and your other tools pass information back and forth.
Token
The unit AI tools measure (and bill) text in, roughly three-quarters of a word. Most AI usage costs are counted in tokens.
Fine-Tuning
Further-training a general AI model on your own examples so it better matches your style, terminology, or specific task.
Generative Engine Optimization (GEO)
Optimizing your content so AI answer engines like ChatGPT, Claude, and Perplexity can find, understand, and cite your business.
Agentic AI
AI that doesn't just answer questions. It pursues a goal across multiple steps, deciding what to do next and taking action on its own. The shift from AI that responds to AI that gets work done.
Agentic Workflow
A business process where one or more AI agents carry out a sequence of steps, research, draft, decide, act, with a person reviewing the moments that matter instead of doing every task by hand.
AI Coworker
An AI assistant that works alongside your team on real, ongoing work, drafting, researching, summarizing, following up, rather than a one-off tool you open and close. Sometimes called an "AI employee."
Autonomous Agent
An AI agent that can run a task from start to finish with little or no step-by-step human direction. The more autonomy it has, the more important clear guardrails and review become.
Orchestration
Coordinating multiple AI tools, agents, and data sources so they work together on a larger job, like a conductor keeping each part in time.
Multi-Agent System
Several specialized AI agents working together, each handling part of the job and handing off to the next, useful for complex work no single agent should own alone.
MCP (Model Context Protocol)
An open standard that lets AI assistants securely connect to your tools and data, so an agent can actually act inside your systems instead of just talking about them. The connector on your side is called an MCP server. It safely exposes one tool or data source (your CRM, calendar, or documents) for the AI to use.
Plain Answer
Confused by the jargon? That's the point of it.
Most AI vocabulary exists to sound impressive, not to help you decide. If a term matters to your business, it should be explainable in a sentence. If a vendor can't do that, be skeptical.
Next Step
Skip the vocabulary. Find the opportunity.
You don't need to learn the terminology to benefit from AI. Start with the complimentary snapshot, and we'll translate the opportunity into plain business language.