Combining AI with RPA is sometimes referred to as hyperautomation. Machine learning models can be inserted into RPA workflows to perform machine perception tasks, like image recognition: tasks that the human brain can perform in under a second, whose output can be plugged into a larger flow of business logic. Given the graphical nature of RPA, deep learning’s image recognition capabilities are suited to some sub-tasks in RPA. RPA can be optimized for some GUI actions by applying machine-learning and deep-learning algorithms to perception problems, like recognizing a button or an edit field. While the acronym RPA stands for robotic process automation, there are no physical, Boston Dynamics-style robots involved here – the “robots” are software agents that, like all software, do work in a digital space, processing inputs and data.įor example, an RPA engineer can look at a series of tasks taken in a GUI, such as cursor moves and buttons clicks, formulate that series of actions in an RPA wireframe that translates to code, so that those tasks can be performed without human intervention in the future. RPA automates business workflows, or clerical processes, by emulating human interaction within a graphical user interface (GUI).
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