Robotic Process Automation (RPA)
Robotic Process Automation (RPA) uses software robots that automatically carry out rule-based, repetitive tasks on existing user interfaces, the same way a person would at a keyboard.
An RPA bot operates existing applications the same way a person would: it opens programs, clicks buttons, reads fields, and enters values into forms. It doesn't need a programming interface for this; it works directly on the same user interface a human would see. The bot follows a fixed, predefined set of rules along the lines of if condition A occurs, carry out step B, which sets RPA apart from classic system integration, where software talks directly to other software through interfaces.
Typical use cases are tasks that recur often, are clearly structured, and leave little room for error: pulling invoice data out of PDF documents and entering it into the accounting system, processing order confirmations that arrive by email, reconciling master data between two systems, or pulling together reports from several sources. RPA is often paired with optical character recognition so it can also handle unstructured documents like scans or photos. RPA pays off especially where older systems without a modern interface have to stay in place because a real integration would be too expensive or too risky.
RPA isn't artificial intelligence in the strict sense. A classic bot doesn't learn on its own; it follows rigidly programmed rules, so if an application's interface changes, say through a software update, the bot can break and needs to be reconfigured. Modern RPA platforms increasingly combine rule-based automation with AI building blocks like text recognition or classification to handle exceptions more flexibly. For structured, high-volume processes with clear rules, though, plain RPA is still often the simpler and cheaper option.
Practical Example
A mid-sized trade business receives around 300 supplier invoices a month by email and post; until now, each one had to be entered by hand into the accounting system by a staff member, taking about 6 minutes per invoice on average. An RPA bot now reads the invoices automatically, picks out the supplier, amount, and invoice number using text recognition, and enters the data straight into the system. The staff member only checks exceptions, cutting the monthly workload from around 30 hours to about 6, with the freed-up time going into resolving disputed cases and supplier calls.
How Leanshift Helps
RPA closes media breaks that quietly eat up time in many processes: data copied by hand between systems doesn't just cost minutes, it also creates error sources and waiting time. From a kaizen perspective, RPA is only worth looking at once the underlying process itself is understood and stabilized; otherwise you're just automating the existing waste faster. Used well, RPA frees up capacity for the work that actually drives improvement: judging, asking questions, thinking further.
Frequently Asked Questions
Is RPA the same as artificial intelligence?
No. Classic RPA follows fixed rules defined by people and doesn't learn on its own. Only when RPA is combined with AI components like text recognition or classification can it also handle exceptions and unstructured data.
Does RPA replace jobs?
RPA mainly takes over repetitive, rule-based subtasks, not entire roles. In practice, work tends to shift toward tasks that require judgment, handling exceptions, or dealing with customers.
What does a business need to introduce RPA?
The starting point is a clearly documented, stable process with unambiguous rules. Without a properly described workflow, automation usually just makes the existing chaos run faster.