An AI copilot helps a person do the work: it suggests, drafts, and answers, and the person decides and acts. An AI agent does the work: it takes a goal, plans the steps, uses tools and APIs, and only pulls in a human for approvals or exceptions.<\/p>\n
That’s it. Same underlying models, very different jobs.<\/p>\n
Here’s the part most explainers skip: the difference is a deployment choice, not a model choice. The same large language model can sit beside you as a copilot in the morning and run unattended as an agent at night. What changes is who starts each step, who checks the output, and who owns the result.<\/p>\n
An AI copilot is an assistant embedded in the tool you’re already using that responds to your prompts and context. An AI agent is software that receives a goal and works through a plan – calling tools, checking results, and adjusting until the goal is met or it needs a human.<\/p>\n
An AI copilot is a collaborative assistant. You give it a prompt or open a file, and it generates drafts, suggestions, code, summaries, or answers in that context. Then it stops. Control comes straight back to you.<\/p>\n
Think of it as a sharp junior colleague who never touches the keyboard without permission.<\/p>\n
Not sure if you need a copilot or an agent?<\/p>\n
Tell us about one workflow. Our AI team will map the steps, the systems involved and the risk, then recommend the right level of autonomy: a copilot, an agent, or a mix of both.<\/p>\n
Talk To An AI Expert<\/a><\/p>\n<\/div>\n An AI agent works from a goal rather than a single prompt. It breaks the objective into steps, picks the tools or APIs to use, runs them, watches what happens, and keeps going. It loops in a person only for major decisions, exceptions, or final sign-off.<\/p>\n If a copilot is the junior colleague, an agent is the colleague you hand a task to on Monday and check in with on Wednesday. (For the full picture, see our explainer on what an AI agent is<\/a>.)<\/p>\nWhat is an AI agent?<\/h3>\n
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