Robotic process automation (RPA) and AI agents both take work off people's desks, but they work in very different ways. Choosing the wrong one is the most common reason automation programmes stall.
How RPA works
RPA bots repeat the same clicks and keystrokes a person would make, following fixed rules. They are excellent when inputs are structured and predictable, such as copying values from one system to another on a schedule.
- Strengths: predictable, auditable, quick to build for stable screens
- Weaknesses: breaks when screens change or inputs vary, cannot read unstructured documents well
How AI agents work
An AI agent understands a goal, reads unstructured inputs such as emails and PDFs, decides the next step within rules you set, and uses systems through APIs. It can ask a person for approval before acting.
- Strengths: handles variety, reads documents and language, adapts to exceptions
- Weaknesses: needs evaluation, guardrails and monitoring to stay reliable
A simple test
- If the input is always the same format and the steps never change, start with RPA.
- If the input arrives as emails, PDFs or free text, or the right step depends on judgement, use an AI agent.
- If both are true, combine them: the agent understands and decides, and RPA or an API performs the system steps.
What to measure
Whichever you choose, agree the measures upfront: cycle time, cost per transaction, error rate and the share of cases handled without a person. A short pilot on one process shows the real numbers before you scale.
AI Readiness Assessment
Two weeks, fixed scope: ranked AI use cases, data and risk check, and a pilot plan.
See what's included
