Robotic Process Automation (RPA) is highly sought after by businesses to advance their automation journey. RPA bots are capable of accurately executing a high volume of repetitive, rule-based actions. To level-up your RPA solutions, applying critical thinking abilities is a must. Integrating RPA technologies with Artificial Intelligence can be a game changer for businesses.
The Impact of Adding Intelligence to RPA
Robotic Process Automation carries out basic tasks that do not require thought or insights; tasks such as coding, routine, or practical computing tasks. RPA's central concept is to do what the developer has instructed and relies significantly on human guidance and maintenance. The goal of adding AI is to let the software robots think and learn for themselves.
RPA based automation purely depends on the data provided, if the data provided is biased and incorrect, then the tasks executed will be incorrect. It is crucial to check for data bias when implementing RPA tools. By parsing data through AI tools, data can be cleaned and prepared. AI can dive into multiple layers of data to scrutinize the relevant information. To segregate data, it is important to define parameters which form the basis to train machine learning models. Integrating RPA and AI in this way can improve accuracy and efficiency of automation efforts. By analyzing the environment, the models learn from their mistakes and accordingly reprogram the models.
If the RPA bots employed are for customer interaction, then AI-powered RPA bots can understand the unstructured data from the customer's natural language using NLU models. The intelligence-powered bot can reply to customers appropriately while tailoring the experience to each individual customer.
The use of RPA with AI is also combined in UiPath's Computer Vision, where the bot identifies and interacts with fields and components on the screen (including PDFs and images) and has the capabilities to accomplish text analysis.
There are many use cases where AI can be integrated with RPA to enhance tasks and remove the need for human workers. The success of this integration depends on the organization's ability to strategically plot the business application. Success can be measured by how fast you reach ROI or a break-even point.
Conclusion
RPA and AI integration can scale up business capabilities. All they need is a strategy defining the integration and the right RPA vendor who understands the overall automation strategy. Adoption of AI in RPA enhances productivity, efficiency, and thus ROI. The automation industry as a whole is growing and evolving quickly. This is the best time to invest in this technology and earn a high return for the future.
About Author
Shireen Khan works as Senior Test Automation Engineer at V-Soft Consulting, and has more than 7 years of IT experience as RPA Developer and Software Development Engineer in Test. She is certified professional in “UiPath - RPA Developer Advanced Certificate”. She is proficient in Blue Prism, UiPath, Selenium WebDriver, TestNG, Maven, HP-UFT, HP-ALM, Git – GitHub, GitLab, Galen Framework, Rest API, Postman, Appium, and Jenkins.
