Artificial Intelligence (AI)

Robotic Process Automation is a process automation technology that uses software robots or digital workers to automate repetitive tasks, 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 executes repetitive work.

 

Artificial intelligence analyzes the actions of machines, 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) has made a big impact globally by increasing efficiency, productivity and profitability across all industries. Today, RPA is no longer limited to predefined tasks and data. Artificial Intelligence (AI) based “cognitive BOTS” are capable of handling ambiguity and make decisions for the most part like their human counterparts.

 

Combination of RPA & AI mimics human activity through machine vision, speech recognition and pattern detection capabilities and can handle structured, semi-structured, and unstructured data. Machine Learning lets BOTS learn how to process as well as improve processes that lead to probabilistic behavior.

AI

RPA and AI are two horizontal technologies that are distinct in their goals and interfaces.

  • The Role of RPA is to save workers time and RPA is built by RPA engineers via a GUI, or a graphical interface, which they use to arrange the sequence of tasks RPA automates. For the most part, RPA is based on rules, or if-then statements that tell a program what to do under certain conditions
  • AI is an umbrella term that includes rules engines like the kind mentioned above. But that’s not the exciting side of AI, and it’s usually not what people mean when they refer to AI.  AI can be 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, sometimes it makes decisions based on a bunch of numeric parameters that it arrived at after much trial and error.

 

Advances in AI allow us to make more accurate decisions about the data we’re 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 in RPA could include image recognition or text analysis, etc.

 

Here are two examples of how incorporating AI into RPA solutions can make the technology even more efficient.

Cognitive-Document-Automation

Cognitive Document Automation (CDA)

CDA processes structured and unstructured content, especially in business processes 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, web portals or physical paper. CDA delivers the greatest accuracy, efficiency and consistency and dynamically adapts to your evolving processes

Intelligent-Screen-Automation

Intelligent Screen Automation (ISA)

ISA uses artificial neural network to analyze an image of an application. For example, where applications are running on Citrix or other remote desktop environments and only image information 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 an RPA solution to connect and work with environments that only return image information back. 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 robot 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

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 or several chatbot services can be easily leveraged by an enterprise-class RPA solution. I n those cases, AI is consumed as a service to help the BOTS to intelligently perform tasks.

 

How does it work?

RPA automates manual work of collecting information. AI automates the “head” 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 more and faster decisions.

RPA and AI together make up the new smart digital workforce that frees human workers to be more effective at their work and help to make better decisions.