If you've spent any time researching accounts payable automation, you've probably run into the term RPA, robotic process automation. It's one of the oldest and most widely deployed forms of business automation, and it still plays a real role in AP departments today. But it's also frequently confused with newer, AI-powered approaches to invoice processing. This guide breaks down what RPA actually does in accounts payable, where it holds up, and where it runs out of road.
How RPA works in AP
RPA works by recording and repeating a fixed sequence of actions, the same way a human would perform them. In an AP context, that might mean a bot logging into a vendor portal, copying an invoice number and amount into a spreadsheet, or pushing that data into an accounting system field by field. The bot doesn't understand what an invoice is. It just follows the same clicks and keystrokes every time, based on rules a person configured in advance.
This makes RPA useful in environments where systems don't talk to each other and building a proper API integration isn't feasible. If your ERP has no API, or a vendor portal doesn't support automated data exchange, an RPA bot can act as a stand-in for a person manually doing that work.
What RPA does well
Where RPA earns its keep is repetitive, rule-based, structured-data work: same layout, same fields, same steps, every time. It's fast to set up against a process that isn't going to change, and it doesn't require you to rip out or replace legacy systems. It just automates the manual clicking around them.
Where RPA hits its limits in AP
The catch is that RPA has no way to adapt. It doesn't read or understand a document; it just looks in the same place on the screen or file every time. The moment a vendor changes their invoice template, or a new supplier sends something in an unfamiliar format, the bot either fails outright or extracts the wrong data silently, which is worse. Every new format, every exception, every edge case means someone has to go back and reprogram the bot by hand.
This isn't a theoretical problem. A December 2025 study by Artificio, spanning 500,000 document-processing transactions across healthcare, finance, logistics, and real estate, found that AI agents outperformed RPA by 40% on unstructured document processing, with the largest gap appearing on exactly the kind of documents AP teams deal with daily: multi-page invoices, inconsistent layouts, and vendor-specific formatting. Healthcare deployments in the study saw 94% extraction accuracy with AI agents versus 61% for RPA on variable forms.
Source: Artificio study, reported via ERP Today, December 2025.
RPA vs. AI-powered document processing
The distinction comes down to what each technology is actually built to do. RPA automates repetitive actions across systems; it's the digital equivalent of a very fast, very literal-minded assistant clicking buttons in the same order every time. AI-powered intelligent document processing (IDP), by contrast, is built to read and understand the content of a document itself, regardless of its layout or format.
Aspect | RPA | AI / Intelligent Document Processing |
|---|---|---|
How it handles documents | Follows fixed rules and screen locations | Reads and understands document content |
Adapts to new invoice formats | No — breaks and needs reprogramming | Yes — adapts without manual reconfiguration |
Best suited for | Stable, structured, repetitive tasks | Variable, unstructured, exception-heavy tasks |
Learns from corrections | No | Yes |
This is why AP automation has shifted so heavily toward AI/IDP over the last several years: invoices are exactly the kind of document that breaks RPA's core assumption of "the same thing, every time." Astera's platform is built on this AI/IDP approach rather than RPA's screen-scripting model. It extracts and validates invoice data by understanding it, not by repeating fixed clicks.
See how AI invoice processing handles invoice layouts that RPA cannot.
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