RPA or AI agents: which automation for your processes?

RPA proved automation was worth it. But replaying clicks on screens has limits: the moment a document changes or a case falls outside the script, the robot breaks. AI agents approach the problem differently. An honest comparison.

0

scripts to maintain when a layout changes

5 steps

of pipeline, from file drop to deliverable

100%

of AI calls metered, capped and billed at real cost

Two different logics

RPA (Robotic Process Automation) replays human actions on interfaces: open a screen, copy, paste. It excels when everything is stable, and seizes up the moment a format moves. Every screen or layout change is paid for in script maintenance.

An AI agent doesn't replay clicks: it understands content. A new but similar document gets processed; a doubtful case gets flagged instead of failing the batch. That's the ERHA logic: pipelines that read, process, verify and deliver, with a human keeping the final call.

The comparison, point by point

Classic RPAAI agents · ERHA

Heterogeneous documents

One script per layout, to maintain.

Structure is understood, not scripted.

Edge cases

The robot fails, or processes silently.

Flagged and submitted for human validation.

Setup

An RPA project: licences, developers, weeks.

Pipeline built by ERHA on your real files.

Maintenance

Scripts reworked at every change.

The pipeline absorbs format variations.

Costs

Per-robot licences, fixed cost.

Per run: metered, capped, billed at real cost.

Choosing in practice

RPA remains a fit if

  • Your screens and formats never change.
  • Volume justifies a dedicated full-time robot.
  • No interpretation is ever needed, at all.

AI agents win if

  • Your documents vary from one issuer to the next.
  • Doubtful cases must be seen by a person.
  • You want to pay per run, not per licence.

Frequently asked questions

Do we have to drop our existing RPA?

No. The two coexist well: RPA carries on with the stable flows, AI agents take the variable documents and the cases that need interpretation. Most teams start with a single process.

Is an AI agent reliable enough for a business process?

The ERHA pipeline doesn't guess: doubtful cases are re-checked, then flagged for human validation, and every decision is traced. Reliability comes from control, not blind trust.

How does an AI agent's cost compare with an RPA licence?

There is no licence: every AI call goes through the Token Gateway, metered, capped and billed at real cost. You see the cost of each run and compare it with the human time or licence it replaces.

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