1 Executive Summary

The initial wave of RPA technologies focused on automating manual, repetitive tasks such as data entry automation using screen scraping. But RPA is increasingly using AI (mainly in the form of machine learning) for augmenting and replacing human decision making and understanding of text and other information for more complex and enterprise-wide applications.

What distinguishes RPA from traditional IT automation is the ability of adapt to changing circumstances and exceptions, and its ability to integrate workflows across an entire enterprise. This approach enables companies to integrate siloed operations, applications and data, build internal capabilities to adapt and scale, and create business value and competitive advantages. RPA uses pieces of software capable of completing complex repeated processes typically performed by a human. These pieces of software are commonly called “software robots”.

RPA typically mimics the tasks performed by humans, but a digital workforce of software robots can also support and augment business processes and human workers as well as manage processes across multiple departments, locations, and systems, on premise and in the cloud.

The biggest benefit of software robots is that they are not prone to human error, can easily scale to workloads and work 24x7 every day of the year.

By replacing humans for high-volume IT and business processes, RPA is not only about improving efficiency and productivity, cutting costs and reducing headcount, but it is also about freeing up employees for more strategic and rewarding tasks, and is ultimately about enabling organizations to grow and remain competitive or even gain a competitive advantage.

This leadership brief outlines the main use cases for RPA to help businesses assess the relevance of RPA and how it can be applied as well as avoid potential pitfalls.