One of the main reasons why people don’t use AI is because they don’t understand what AI means.
There are too many buzzwords, types of tools, and interchangeable definitions.
“AI” sounds too vague, too technical, or too much like science fiction to even want to try to wrap your head around it.
But AI isn’t as complicated as it seems once you know basic terminology.
To help you enter the AI conversation and unlock your own AI use, let’s dig into the terms you need to know.
What Is AI?
AI or artificial intelligence is any software that enables computers and programs to perform tasks that normally require human thinking (such as understanding language, recognizing patterns, making decisions, and taking action).
AI is an umbrella category that can refer to any type of AI tool, technology, or training model.
What Is Machine Learning?
Machine learning is the technology that lets AI improve at a task by studying data instead of following a fixed set of rules someone typed in.
Machine learning is one specific approach to building AI. It’s what is behind most AI software today.
A traditional computer program does what it’s told, step by step. A machine learning model is shown thousands (or millions) of examples and picks out the patterns on its own. The more examples it sees, the better it gets at recognizing what matters and predicting what comes next.
What Is a Large Language Model (LLM)?
A large language model (LLM) is a machine learning model trained on massive amounts of text so it can understand and generate human language. ChatGPT and Claude are both built using LLMs.
An LLM is machine learning applied specifically to language. Instead of learning patterns in numbers or images, it’s learned patterns in billions of words from books, websites, and articles. That training lets it write coherently, answer questions, translate languages, and hold conversations that feel surprisingly natural.
When you type a prompt into Claude or ChatGPT, you’re talking to an LLM. It’s not “thinking” the way humans do — it’s predicting the most relevant and useful response based on everything it’s been trained on.
What Is Generative AI?
Generative AI is any AI tool that creates new content (such as text, images, audio, or video) based on a prompt or instruction.
Generative AI doesn’t just retrieve information (like a search engine does). It generates something new. You ask it a question or give it a starting point, and it produces something original in response.
Examples of generative AI in action:
- You describe your business, and it writes a homepage headline.
- You upload a photo, and it creates five variations with different backgrounds.
- You summarize a meeting in bullet points, and it drafts a follow-up email.
Claude and ChatGPT are both generative AI tools as they produce new content based on prompts.
What Is a Chatbot?
A chatbot is software you interact with through a conversation interface. You type or speak in natural language and get a response back. An AI chatbot is a conversational tool powered by LLMs.
Chatbots have been around for years. You may have used them on websites. Older model chatbots acted like a two-way conversation but they were based on rules-based prompts. They were trained on specific information and were limited in what information they could deliver.
Newer AI-based and generative chatbots (like Claude and ChatGPT) are built on LLMs that expand their ability to answer any question.
What Is an AI Agent?
An AI agent is a single AI system that pursues a goal on its own. It can make decisions and take action (such as searching the web, pulling data, drafting content) without you directing each step.
This is where AI moves beyond simply answering questions or generating content.
An AI agent can take control over computer programs and applications and take action. It is given a goal, and it figures out the steps needed to accomplish that goal, often using multiple tools to get there.
What Is an Agentic Workflow?
An agentic workflow is a series of AI-driven tasks that run automatically to complete a larger goal.
An agent and a workflow describe the same idea from two different angles. Think of an AI agent as an employee, and an agentic workflow as that employee’s set routine.
An agentic workflow is a similar to automation, but more powerful.
Traditional automation is rule-based: “When X happens, do Y.” AI-powered workflows can handle more complex decisions, such as: “When X happens, figure out the best version of Y based on context.”
What Does “AI-Powered” Mean?
AI-powered means a tool or feature has AI built into it. It is using machine learning or LLMs to improve or automate part of what it does.
You’ll see this phrase everywhere now. AI-powered writing assistant. AI-powered scheduling. AI-powered CRM.
When a tool is genuinely AI-powered, it typically:
- Gets smarter or more personalized over time
- Can interpret natural language (plain English) instructions
- Generates, predicts, or recommends something, rather than just retrieving or sorting
- Reduces the manual decisions you have to make
Putting It All Together
| Term | Definition |
| AI | Any technology that performs tasks that normally require human thinking |
| Machine Learning | Technology that uses data to continuously improve |
| LLM | A language-based machine learning model |
| Generative AI | AI that creates new content from a prompt |
| AI Chatbot | AI you interact with through a conversation interface |
| AI Agent | AI that takes action toward a goal on its own |
| Agentic Workflow | AI-driven tasks that run automatically |
| AI-Powered | A tool that uses AI to work smarter or faster |
Get Over AI Overwhelm
AI terminology can be challenging, but that doesn’t mean AI has to be.
AI is becoming more and more user-friendly and accessible. You may even be using it already without knowing it.
If you are interested in learning more about using AI in your workflows, let’s chat. Send me a message and let me know where you are stuck.
