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RPA or AI agents: what is the difference and which do you need?
Robotic process automation (RPA) repeats steps someone recorded. An AI agent reads each case and decides what to do next. They suit different jobs, and in either case the important decisions should still have a person behind them.
Book a discovery call| Question | RPA | AI agents |
|---|---|---|
| How it works | Repeats a fixed set of recorded steps, often by clicking through screens. | Reads the information, picks a step using rules and a language model, then acts in your software. |
| Best at | High-volume work that is identical every time. | Work that varies from case to case, such as emails, invoices and requests. |
| Unexpected input | Typically stops or errors when something differs from the recording. | Can interpret it, and should stop and ask a person when it is unsure. |
| When a screen changes | Scripts that depend on the screen layout often need repair. | Less tied to a layout, though it still needs testing when tools change. |
| Main risk | A silent break when something changes. | Acting confidently on bad data or guessing when it should ask. |
| Controls to add | Monitoring and alerts when a run fails. | Rules written down, approvals for important steps and a record of every decision. |
When RPA is enough
If the work is the same every time, such as copying a fixed set of fields between two systems, recorded steps are a sound and predictable answer. Add monitoring so that a failure is noticed quickly.
When an AI agent fits better
- The information arrives in different forms, such as supplier invoices in many layouts.
- The next step depends on what the item says, not only where it came from.
- People currently spend time reading, checking and chasing before a simple decision.
Why both need a person behind them
Neither technology should make decisions that are hard to undo on its own. With RPA the risk is a quiet failure. With an agent it is a confident wrong answer. In both cases, set rules you have approved, make important steps wait for a named person, and keep a record so you can explain what happened. Our guide to human-in-the-loop automation covers where to put the approval, and human-in-the-loop AI shows how we build it.
Combining them
Some systems use an agent to read and prepare each item and a fixed integration to carry out the final step. We start by mapping the work and choose the simplest tool that does the job safely. If you are comparing against simple app-to-app tools, see Zapier, Make or n8n vs a custom AI workflow.
Questions people ask
Is an AI agent a replacement for RPA?
Not always. RPA is still a sound choice for work that is identical every time. Agents are a better fit where cases vary and someone has to read and decide.
Are AI agents less reliable than RPA?
They fail differently. RPA tends to stop when something changes. An agent can act on a wrong reading, which is why it needs rules, approvals and a record.
Can I keep my RPA and add an agent?
Yes. An agent can read and prepare an item and hand it to the existing step. We map the work first and keep what already works.
How do I start?
Pick one part of the business where work gets stuck and book a 30-minute discovery call. You get a straight answer on whether a system would help.