Robotic Process Automation and cognitive technologies, already adopted in many industries worldwide, have improved business processes and increased customer experience.
RPA is at its core a technology that automates repetitive, mundane, or rules-based tasks that would otherwise require a lot of human effort. But, the only disadvantage of that technology is that RPA is not intelligent by itself. To truly drive Intelligent Automation, enterprises must converge RPA and cognitive technologies such as Artificial Intelligence and Machine Learning (ML). This combination will enhance the RPA’s proficiency with AI’s thinking abilities that imitate human behavior.
Once organizations have implemented Intelligent Automation, they can chart a path toward hyper-automation. Thus, Automation can take complex and high-risk activities across the entire enterprise.
How does Intelligent Automation work?
Intelligent Automation can complete tasks that require creativity, intuition, judgment, or problem-solving. Rapid developments in Artificial Intelligence are driving the development of new cognitive technologies that have human-like abilities such as recognition of handwriting, identification of images, and natural language processing. When combined with powerful analytics and Robotic Process Automation, these cognitive technologies can create Intelligent Automation solutions that either assist people in non-routine tasks or completely automate them.
Three use cases of Intelligent Automation
· Boosting efficiency in the back-office
AI-enhanced RPA allows organizations to automate real-time inventory management. This robot can access the company’s CRM and extract inventory data. Then, it can use an ML model that predicts next week’s sales figures. Once it calculates the forecasts, the robot will notify a human about the future need for inventory. The human will then need to give the purchase order to the bot to place the order.
· Enhancing Customer Experience
Cognitive robots have already succeeded in solving customer experience-related business problems. This year, Gartner expects 70% of customer interactions to involve cognitive technologies such as ML.
Organizations can use conversational agents to provide robots intelligently understand the customer’s intent. They work with back-end enterprise systems to quickly resolve their queries and claims and significantly improve the customer experience.
· Maximizing Sales Capabilities
RPA, besides AI, can be used to help sales teams in all industries by deploying cognitive robots capable of performing predictive analysis using Machine Learning models and generating new data that predicts future market behavior.
Organizations can use Intelligent Automation to predict outcomes. They can then plan the best course of action. With data, robots can identify leads that are most likely to convert.
RPA is the first milestone to Intelligent Automation.
Robotic Process Automation can complete repetitive tasks like data entry or other paperwork. AI or other cognitive technologies then enhance this technology. Thus, Intelligent Automation systems can automate redundant, rule-based tasks using highly-structured data. Moreover, it can extract valuable information from unstructured data and learn more about a process through comprehending more data. But the most important fact is that RPA is the foundation of all Intelligent Automation systems.
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