The AI Glossary: Demystifying Terms You Need to Know

AI doesn’t need to feel like a riddle wrapped in a mystery. This glossary is here to clarify the terms you’ve been hearing and help you understand what they mean for you and your work. By the time you’ve finished, you’ll feel ready to talk about AI with confidence—whether in a team meeting, brainstorming session, or casual chat.  

AI isn’t just for experts. It’s for anyone curious about making smarter, faster, and better decisions. Let’s break it down together.  

Artificial Intelligence   

Artificial intelligence (AI) is a broad term that refers to the technology enabling computers and other machines to perform tasks typically requiring human intelligence. These tasks can include spotting patterns in data, making predictions, or even responding to your questions in real time. You can think of AI sort of as the brains behind the tools you use to help you work smarter and tackle challenges in new ways. 

Generative AI  

Generative AI is a form of AI that creates something entirely new—whether it’s a text-based report, an image, or even a piece of music—based on what it has learned from data. Popular tools like ChatGPT and DALL·E are some examples of this technology. Generative AI’s ability to move beyond analysis and actually produce original content can help with everything from creative brainstorming to drafting emails. 

Machine Learning (ML)  

Machine learning is a way for systems to improve their performance by learning from data. Imagine training a machine to predict customer trends by analyzing past behavior, improving its accuracy over time as it processes more information. It’s one of the key methods that make AI systems smarter. 

Large Language Model (LLM)  

Large Language Models are advanced AI systems trained on extensive sets of data, such as text from books, studies, online articles, transcriptions and more. Because they learn from such massive troves of text data, these models are able to grasp the patterns and nuances in grammar and language. This enables them to perform complex tasks like summarizing a transcript from a call or translating an email into a different language. Chatbots, for example, can use LLMs to generate natural-sounding responses to questions, providing users with a human-like conversational experience.    

Retrieval-Augmented Generation (RAG)  

RAG combines the creative power of AI with real-time data retrieval. This AI framework improves the answers generated by an LLM by providing it with outside sources of data that may be more relevant. Think of it as pairing an AI’s ability to generate content with live, accurate information. For instance, RAG can pull the latest sales data while helping craft a business summary, ensuring that the output is current and reliable. 

Agentic AI  

AI doesn’t just create content; it can also power your processes and solve your workflow problems. Agentic AI systems are able to understand your goals, reason through which actions should be taken to achieve your objectives, and execute on those decisions. Because these systems can operate independently, agentic AI can help you work more efficiently and free up your time to devote to more important tasks. 

AI Agents  

If “agentic AI” describes the concept of powering your workflows with AI, AI agents are the tools that make this idea a reality. AI agents are the specialized systems that perform the actual tasks like problem-solving and execution. They use LLMs to understand and respond to what a user might ask of them, and they also know when to use external tools to achieve their goals. Another benefit of AI agents in that they learn from interactions, so they get better over time at meeting your expectations.  

Multi-Agent Systems in AI  

In a multi-agent system, different AI agents work together to achieve more complex goals. Each agent has a unique role—one might analyze customer trends while another forecasts inventory needs. Together, they share resources and learn from each other, which allows them to take on more challenging tasks and perform better than they would individually. 

AI Agent Marketplace  

An AI agent marketplace functions like an app store for automation. Instead of coding your own solutions, you can browse, select, and deploy pre-built AI agents designed to handle specific workflows. It’s a faster, easier way to put AI to work without needing deep technical skills. 

Making AI work for you  

AI might feel overwhelming at first, but it’s really just a set of tools designed to help you get more done with less effort. Whether you’re looking to automate repetitive tasks, improve decision-making, or uncover insights, AI can make it happen.  

And you don’t need to figure it out alone. Domo’s AI capabilities are designed to be approachable and practical, so you can focus on the outcomes—not the learning curve. Let’s also explore some of the terms you might come across as you learn more about all that Domo has to offer in this arena.  

Domo.AI 

You can think of Domo.AI as an umbrella term for all of our AI capabilities.  

AI Service Layer 

Domo’s AI Service Layer is our flexible AI framework built to simplify and streamline data exploration in your dashboards and apps. The AI Service Layer provides access to a variety of services such as text generation and summarization, and gives you a space to create and train your own AI models.  

DomoGPT 

ChatGPT is built on LLMs that pull data from publicly available sources, third parties, and its users. To ensure that data from Domo users remains secure, we built DomoGPT, which uses a suite of Domo Cloud private models to keep your data within the Domo ecosystem, protected from third-party access.  

AI Chat  

This personal data assistant works as a pop-up window that allows you to ask questions about your data and receive answers in real time, which can include new graphs and charts that you can save. AI Chat also provides you with a breakdown of how it generated the answer so that you can verify its processes.  

AI Agents 

Gain access to a suite of specialized AI agents designed to handle a variety of automated tasks. In addition to AI Chat, future AI agents will help generate an app, build a new dashboard, create a workflow, and more. You will also have the option to create your own agent tailored to your unique needs. 

AI Data Dictionary 

Prepare your data sets so that they have all of the information necessary for AI tools to draw insights from them. This new AI-readiness feature helps users add metadata, descriptions, and other data dictionary items that allow the AI Chat agent to return more accurate answers.  

Your next step  

Now that you’ve got the basics, let’s take the next step together. Schedule a meeting with our team to explore how Domo can help you turn these ideas into action.