# Is RPA still relevant now that we have AI?

> Yes. Robotic process automation (RPA) is still the right tool whenever a process is deterministic — the same fixed steps, every time, with no reading or judgment involved. It's often cheaper, faster, and more reliable than AI for those steps precisely because it's predictable. The mistake is treating it as RPA versus AI. The strongest systems use both: RPA for the rules-based steps and AI for the parts that need to read messy inputs or make a call — in one workflow.

_Source: https://plenaura.com/answers/is-rpa-still-relevant-with-ai · Last updated: 2026-06-03 · Plenaura_

The claim that AI made RPA obsolete is buzz, not engineering. RPA automates deterministic, rules-based steps — click this button, copy that field, paste it into another system — and when a process genuinely never varies, that predictability is a feature, not a limitation. A rules-based bot does exactly the same thing every run, is easy to audit, and doesn't carry the cost or the small-but-real error rate of asking a model to do work that doesn't need judgment. For that slice of the world, RPA is still the correct and often the cheapest answer.

Where RPA legitimately falls down is the moment inputs stop being uniform. A bot that expects a field in a fixed place breaks when the invoice arrives as a scanned photo, the form is free text, or the same information shows up in ten different layouts. It also can't make a judgment call the rules don't cover. That brittleness is real — and it's precisely the boundary where AI earns its place, because reading messy, unstructured inputs and deciding what to do with them is exactly what AI is good at.

So the useful question isn't "RPA or AI" — it's which part of the process is deterministic and which part needs judgment. Map a real workflow and it's usually a mix: fixed steps that RPA should own for reliability and cost, and reading-or-deciding steps that AI should own. Bolting AI onto a purely deterministic task adds cost and unpredictability for no gain; forcing RPA to handle variable inputs guarantees breakage. The engineering is in drawing the line correctly and letting each tool do what it's best at.

In practice the two live in one system. A well-built automation uses RPA for the deterministic movement of data and AI for the intake and judgment, with a human review queue catching the uncertain cases so nothing fails silently. Treating RPA as obsolete throws away the cheapest, most reliable half of that design. RPA isn't yesterday's technology — it's one of two tools, and knowing when a process never varies is what tells you to reach for it.