Unlike rule-based RPA, which breaks the moment an input falls outside the script it was given, an AI agent can read unstructured input, reason about what to do with it, coordinate across multiple systems, and handle the exception itself rather than routing it to a human queue.
What makes it different from a chatbot or a script
The distinction is state and control flow. A single prompt-and-response chatbot has no memory of the steps before it and no way to plan across them. A LangGraph-based agent maintains context across a multi-step process, can branch based on what it finds, and produces an auditable record of what it decided and why, which is the part enterprise buyers in regulated industries actually need before they will trust it with a real process.