![]() Robotic process automation is often mistaken for artificial intelligence (AI), but the two are distinctly different. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way. You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and "learning," respectively. Intelligent process automation demands more than the simple rule-based systems of RPA. This type of automation expands on RPA functionality by incorporating sub-disciplines of artificial intelligence, like machine learning, natural language processing, and computer vision. In order for RPA tools in the marketplace to remain competitive, they will need to move beyond task automation and expand their offerings to include intelligent automation (IA). RPA enables CIOs and other decision makers to accelerate their digital transformation efforts and generate a higher return on investment (ROI) from their staff. ![]() This form of automation uses rule-based software to perform business process activities at a high-volume, freeing up human resources to prioritize more complex tasks. ![]()
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