AI agents or RPA: which fits which process

Quick answer

Robotic process automation (RPA) follows a fixed script: it clicks, copies and pastes through screens exactly as recorded. It suits stable, rule based work on structured data, and it breaks when a screen or format changes. An AI agent uses a language model to read unstructured inputs such as emails, PDFs and chat messages, decide what to do next and call your systems through APIs. It suits work that needs judgement, and it needs evaluation and guardrails. Many processes are best served by both: the agent reads and decides, and an API or RPA step posts the result.

How to tell which one a process needs

Ask four questions about the process:

1. Are the inputs structured? A fixed spreadsheet or form favours RPA. Free text emails, scanned invoices and WhatsApp messages favour an agent.
2. Do the steps change from case to case? Identical steps favour RPA. Steps that depend on what the input says favour an agent.
3. Do the target systems have APIs? With APIs, an agent or a plain integration is more reliable than screen scripting. Without them, RPA may be the only route into an old system.
4. What does a mistake cost? High-stakes steps need a person approving the agent's proposal, whichever tool does the work.

Examples

• Copying daily sales from a fixed report into a portal: RPA, or better, a direct integration.
• Reading supplier invoices in many formats and posting them to Tally: an agent with document intelligence, with exceptions sent to a person.
• Answering customer emails about order status: an agent that reads the email, looks up the order and drafts or sends the reply.
• Monthly bank reconciliation with known rules: rules and RPA first, with an agent suggesting matches for the leftovers.
• Triage of support tickets: an agent classifies and routes; staff handle the replies that need care.

Costs to weigh

RPA carries licence costs for the platform and bots, plus maintenance each time a screen changes. Agents carry model usage costs per task, plus evaluation and monitoring. For either one, estimate the hours the process takes today, the share that can be automated and the review time that remains. The AI ROI Calculator does this arithmetic.

Measuring either one

• Straight-through rate: the share of cases finished with no human touch.
• Accuracy: checked on a sample every week, and on every case at first.
• Exceptions: how many go to a person, and why.
• Cost per case: licences or model usage divided by volume.
• Time saved: hours per week, confirmed with the team that used to do the work.

See how to evaluate AI agents before you trust them for a test method.

Questions and answers

Will AI agents replace RPA?

For tasks with unstructured inputs, agents are taking over. For stable screen tasks on old systems, RPA still works well, and agents often call it as one of their tools.

Are agents reliable enough for finance work?

With a person approving the exceptions, a complete activity log and weekly accuracy checks, yes. Start with one process and measure before you widen it.

What should we automate first?

The process that takes the most hours each week, has clear rules for what a correct result looks like, and has an owner who will judge the pilot.