Glossary · IT & systems
AI agent
An AI application that doesn't just answer, but takes steps itself to complete a task. It chooses the tools it needs, calls them, looks at the result and decides what the next step is.
An AI agent is an application built around a language model that carries out a task on its own, step by step. An ordinary chatbot gives you an answer and stops there. An agent goes further: it looks up the data it needs, performs an action in another system, checks what comes back and then decides what to do next.
How an agent reaches your systems
An agent can only do what it is given access to. That access runs through tools: clearly defined actions such as looking up a customer, drawing up a quote or scheduling an appointment. More and more often, those tools are offered through an MCP serverAn open standard that lets AI applications such as Claude, ChatGPT, Gemini or your own AI agent discover for themselves which tools a system offers, and then call those tools. An MCP server usually sits on top of an existing API., which in turn calls your system's API. So the chain is: the agent asks the MCP server, the MCP server calls your API, and your API works with your data.
What it means for your business
An agent can take over repetitive work that today gets stuck between systems, such as retyping data or putting together a file from three sources. It also makes mistakes, and an agent that can write to your systems can also do damage there. So start small. Give an agent read-only access first, and agree on the moments when a person still has to approve before anything changes.
