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Rules engines, RPA bots, and AI agents get pitched as if they compete for the same job. They mostly don't. Each one is good at a different kind of work and bad at the others. This guide gives you four questions to ask about any process, shows where each option breaks, and explains why most finance and operations teams end up running all three side by side.
The two words get used as if they mean the same thing. They do not. One talks to you; the other does the work. Here is what actually separates an AI agent from a chatbot, and how to tell which one a given job really needs.
OCR transcribes an invoice. An agent reads it, checks it against the PO, and only puts its hand up for the ones it can’t justify. Here is what that looks like in a real accounts payable queue.
Most teams ask whether the technology is ready. The better question is whether the work is. These are the five signs I look for before telling anyone to put an agent near their process, and the one that quietly matters more than the other four.
Both promise automation — but one follows scripts while the other rewrites them. Here's why the distinction matters for your operations.
Every business runs on processes. And every process run by humans carries the weight of human fallibility — a miscalculated field, a skipped approval, a missed deadline. AI agents don't eliminate people. They quietly remove the conditions that make errors inevitable. Here's exactly how that works.
If anything in these posts matched a problem you’re sitting on, book a 30-minute discovery call. No deck, no fluff — just a working conversation about your highest-volume paperwork and whether agentic document extraction can make it disappear.
