AI Glossary

Technology that allows software or machines to perform tasks that usually require human thinking, such as understanding language, recognizing patterns, or making decisions.

An AI system that can take actions toward a goal, often by using tools, following instructions, and responding to changing information.

A task-focused agent that uses AI to reason, choose actions, and complete work across systems or data sources.

A set of rules or steps a system follows to solve a problem or complete a task.

A connection that allows different software systems to communicate with each other.

The use of software to complete repeated tasks with less manual effort.

Very large amounts of information that can be analyzed to find patterns, trends, or useful insights.

A pattern in data or system behavior that can lead to unfair, incomplete, or inaccurate results.

A software program designed to perform automated tasks, such as answering questions or processing requests.

The process of turning business data into reports, dashboards, and insights for decision-making.

A software interface that allows people to interact with a system through conversation.

The use of remote servers to store, manage, and process data instead of relying only on a local computer.

A field of AI that helps computers understand and interpret images or video.

The amount of information an AI model can consider at one time when generating a response.

An AI assistant designed to help a person complete tasks faster while the person remains in control.

Information that can be collected, stored, analyzed, or used by software systems.

A system, document repository, database, or application that provides information for an AI tool to use.

A type of machine learning that uses layered models to recognize complex patterns in data.

The process of using digital tools and systems to improve how an organization operates.

AI that can read, classify, summarize, or extract useful information from documents.

Numeric representations of words, documents, or data that help AI systems compare meaning and find related information.

AI designed for business use, with stronger requirements for security, accuracy, governance, and integration.

The process of identifying important names, dates, amounts, companies, products, or other structured details in text.

Training an existing AI model further so it performs better on a specific task, industry, or data set.

A large AI model trained on broad data that can be adapted for many different tasks.

AI that can create new content, such as text, images, summaries, code, or responses, based on patterns it has learned.

The policies and controls that guide how AI is used safely, securely, and responsibly inside an organization.

A type of large language model designed to understand and generate human-like text.

Connecting AI responses to trusted business data or source material so answers are more accurate and traceable.

An AI response that sounds confident but is incorrect, unsupported, or made up.

A workflow where people review, approve, or guide AI output before important actions are taken.

The process of identifying what a user is trying to do based on their message or request.

A connection between software systems that lets data, actions, or workflows move between them.

A centralized collection of information, documents, policies, or answers that teams use to resolve questions.

The practice of organizing company information so people can find, trust, and use it more easily.

An AI model trained on large amounts of text so it can understand, summarize, generate, and transform language.

Short for Large Language Model.

The delay between a user request and the system response. Lower latency means faster answers.

A method of building software that improves by learning patterns from data instead of being manually programmed for every rule.

The trained system that makes predictions, generates responses, or performs a task based on data.

AI that can work with more than one type of input, such as text, images, audio, video, or documents.

A field of AI focused on helping computers understand, interpret, and generate human language.

A type of AI model inspired by connected layers of computation that can learn patterns from data.

Short for Optical Character Recognition. OCR converts text inside images, scans, or PDFs into machine-readable text.

Coordinating multiple tools, systems, prompts, or AI agents so they work together in one workflow.

Internal values a model learns during training that help determine how it responds to inputs.

The instruction or input a user gives to an AI system to guide its response.

The practice of writing clear and effective instructions to get better results from an AI system.

Short for Retrieval-Augmented Generation, a method that lets AI use external knowledge sources before generating an answer.

An AI approach that searches trusted information sources and uses the results to produce more accurate responses.

The process of finding relevant information from documents, databases, or knowledge systems.

The practice of designing and using AI in ways that are safe, fair, transparent, and accountable.

A search method that focuses on the meaning of a query, not just exact keyword matches.

AI that estimates whether text expresses a positive, negative, or neutral tone.

Data organized in a consistent format, such as tables, fields, or databases.

The process of condensing longer information into a shorter, easier-to-read version.

A small unit of text that an AI model processes, such as part of a word, a full word, or punctuation.

The information used to teach an AI model how to recognize patterns and produce outputs.

Controls, citations, permissions, and governance features that help users trust AI-generated answers.

Information that is not neatly organized into rows or fields, such as documents, emails, PDFs, chats, or call notes.

The goal behind a user's question, message, or action.

A database designed to store and search information based on meaning and similarity.

AI that can understand, process, or generate spoken language.

The use of software to complete repeated business tasks with less manual effort.

Short for Explainable AI. XAI focuses on making AI decisions and outputs easier for people to understand.

Asking an AI model to complete a task without giving it examples first.