Artificial intelligence (AI) analyzes the actions of machines and mimics cognitive functions of humans, such as learning and problem solving. AI today includes several technology disciplines such as Machine Learning (ML), Natural Language Processing (NLP), and many others.
Robotic Process Automation (RPA) is a process automation technology that uses Digital Workers or BOTS to automate repetitive tasks and manual processes and augment the work of your employees. RPA interacts seamlessly across desktop software, traditional enterprise browser-based systems, and web sites to aggregate data, transform it into actionable information, trigger responses to communicate with other applications, and execute repetitive work.
Robotic Process Automation (RPA) has made a global impact by increasing efficiency, productivity, and profitability across all industries. Today, RPA is no longer limited to predefined tasks and data. AI-based “cognitive BOTS” can handle ambiguity and making decisions like humans do.
Combining RPA and AI mimics human activity through machine vision, speech recognition, and pattern detection capabilities. This combination can handle structured, semi-structured, and unstructured data. Machine Learning allows BOTS learn how to process, as well as improve processes, that lead to probabilistic behavior.
Difference between RPA and AI:
RPA and AI are 2 horizontal technologies that are distinct in their goals & interfaces. The role of RPA is to save worker’s time. RPA is built by engineers via a graphical interface or GUI, which is used to arrange the sequence of tasks the RPA automates. For the most part, RPA is based on rules; if-then statements that tell a program what to do under certain conditions.
Artificial Intelligence is an umbrella term that includes rules engines like the kind mentioned above. But that’s not the exciting side of AI, and it is usually not what people mean when they refer to AI. AI consists of programs that are capable of rewriting themselves in response to their environment or the data they’re exposed to.
AI is a horizontal technology that makes decisions about data. Sometimes it makes decisions, or predictions, based on rules that humans manually write, and sometimes it makes decisions based on numeric parameters that it arrives at after much trial and error
Advances in AI allow us to make more accurate decisions about the data we are looking at. In some cases, that accuracy can surpass human accuracy.
RPA and AI overlap in that you can infuse RPA with AI. Useful applications of AI powered RPA often include image recognition and text analysis.
Here are 2 examples of how AI-Powered RPA can make technology even more efficient:
Cognitive Document Automation (CDA):
CDA processes structured and unstructured content, especially in business systems that entail the handling of documents. An AI-powered RPA solution can become increasingly efficient over time. As more documents are processed, the solution learns how to intelligently manage variations independently of the channels the information is exchanged through (whether electronic channels like email and web portals, or physical paper). CDA delivers the greatest accuracy, efficiency, consistency and dynamically adapts to your evolving processes.
Intelligent Screen Automation (ISA)
ISA uses artificial neural networks to analyze an image of an application. For example, where applications are running on Citrix or other remote desktop environments, and only image data is available, there is no direct access to the application and its objects. As virtualization is used almost everywhere, this becomes an increasing issue for RPA solutions to connect and work with environments that only return image data. ISA addresses this issue by automatically creating user interface objects for the robot designer to use in building the software robot. This results in significantly faster BOT development and avoids the issue of screen resolution standardization, because the robot does not depend on screen position to select menu items or buttons when performing tasks.
How does it work?
CDA and ISA are the most requested AI technologies to be leveraged with RPA, but there are many more. For example, AI services such as Google Vision, IBM Watson, and several chatbot services can be easily leveraged by an enterprise-class RPA solution. In those cases, AI is consumed as a service to help the BOTS intelligently perform tasks.
- RPA is the “hand”
- AI is the “head”
RPA automates manual work of collecting information. AI automates the brain work by analyzing the information provided by RPA and either making a decision, or making a recommendation, to the human analyst so he or she can make quicker and more frequent decisions.
RPA and AI together make up the new smart digital workforce that frees human workers to be more effective at their jobs and aids in better decision-making.