Robotic process automation (RPA) emulates human actions by interacting with digital systems and software — making it easy to build robots that do things like pull data from a PDF, understand what's on a screen, or complete keystrokes.
Once equipped with artificial intelligence, Robotic Process Automation (RPA) provides companies with huge opportunities to process large volumes of data. This results in highly automated, data-driven operations and replaces manual intervention to control workflows and process unstructured data. In manufacturing environments, RPA simplifies business operations and reduces the risk of errors by automating repetitive tasks and processes — including everything from parts inventory management to assembly lines. Since organizations typically have both structured data (such as form fields) and unstructured data (such as free text, natural language), many processes require RPA and AI to fully automate the end-to-end process.
In its simplest form, RPA is not meant to copy human intelligence. It is intended to simulate elementary human activities, perform repetitive tasks, save resources, and free people from routine tasks. When we combine machine learning and artificial intelligence with robotic process automation we create something we refer to as intelligent automation, or more commonly, hyperautomation.
Hyperautomation (touted by Gartner as a top 10 technology to watch) allows cognitive processes that have been performed manually or semi-manually in the past to be automated with near-perfect accuracy. With hyperautomation, we are able to automate repetitive tasks, increase the level of human perception and prediction, increase the speed and accuracy of work processes, and automate complex business processes. Hyperautomation takes AI to the next level by using tools such as business process management to standardize the approach to automation throughout the organization and create even more business value.
Smart Process Automation (SPA) — sometimes referred to as RPA 2.0 — is a logical evolution of RPA Technology where robots utilize AI and ML to perform cognitive tasks that would otherwise require human intelligence or laborious processes. SPA solutions use cognitive technologies such as speech recognition and natural language processing (NLP) to "learn" how to perform a task based on models and inferences. By creating automated analytical models, machine learning implements computer algorithms that enable them to act by learning from their own experience, so they can accurately predict with data.
Both RPA and SPA are useful tools for a variety of workflows, from simple rule-based processes (RPA) to more complex judgment-based processes (SPA). With accurate data annotations, ML and AI models can make even more accurate decisions, and when combined with the fundamental processes of RPA, they can achieve true intelligent automation (hyperautomation).
For organizations looking to take their RPA to the next level, AI and intelligent automation are a must. Are you ready to start automating all of your repetitive tasks and optimizing your business processes?
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