How do RPA and IA differ in the processes that they can automate?
There are many benefits to RPA, especially when the differences between intelligent automation (IA) are known and each technologies strength is utilized to complement the other. Many of the top RPA tools have enhanced the ability of the technology, although process improvement could require intelligent automation.
IA is an "automation system that can sense and synthesize vast amounts of information that enable it to automate entire processes and workflows", defined by Vivek Mishra (AVP of Technology and Solutions). IA is a broad term used to describe various technologies, including artificial intelligence (AI), machine learning (ML), NLP, Intelligent OCR, and BPM - RPA vs AI, RPA vs BPM.
RPA is the "hands" of the operation, while IA is the "brains" of the operation, based on Erwin De Leeuw's comment. Vivek goes on to explain RPA is best for "automating rules-based activities or just mimicking human action." Tasks like "reading data, entering data, passing data along from one system to another, and extracting data are great for RPA, says Scott Francis, while IA is better suited for "streamlining the processes from end to end", says Mohammad.
Both technologies, RPA and IA, can work together and leverage each other's strengths. IA can optimize processes while RPA can be utilized for more structured and repetitive tasks. Sriram provides great insight by highlighting that "the sophistication of the decision making however depends on the depth of the AI engine itself and the adaptive capacity depends on the functionality of the defined bot." Nonetheless, both IA and RPA working together can automate and optimize your business from both a process and tactical perspective.
RPA is great at emulating what a person would do to read data, enter data, pass data along from one system to another, extract data, inspect data, re-organize that data in a rote way. However, all of these activities can be brittle without adding some intelligence around decisions, intelligence around data extraction, and context of the larger process within which we're automating. Building intelligent automation solutions produces more robust, resilient approaches to the current set of RPA problems, as well as addressing a wider scope of the set of automation issues. In addition, there are use cases for AI and process and decisioning that are limited when they are applied without RPA to automate bits that would currently be handed off (needlessly) to a person to do, undermining the speed, value, and ROI of the solution.
At BP3 we're always looking for the faster way to do that, and Intelligent Automation is the key to how we build solutions for our clients. (www.bp-3.com)
RPA [Robotic Process Automation] will be used for automating rule-based activities or just mimicking Human Action.
On the other hand IA [Intelligent Automation] is the ability of the machine to think so Intelligent automation systems sense and synthesize vast amounts of information and can automate entire processes or workflows, learning and adapting as they go.
IA is like simulation of human intelligence by machines and not like RPA to just mimics the Human actions.
For e,g If I need to process the Invoice Document then using RPA tools we can map the fields for Values.
On Other hand by using IA we can incorporate the intelligence to Bot \Program that if any field mapping is wrong then Intelligent decision making can correct that as well notify the concern dept.\person too.
Hope this helps.
RPA stands for Robotic Process Automation and by definition it means automation of repetitive , mundane tasks done by a user. This implies that the process being automated has to follow a set of rules that do not change. If the rules change then either it is flagged as an exception or the automation fails depending on the coverage of the automation use case.
Typical examples of RPA would be : Extracting Dollar exchange rates or NASDAQ stock prices and exporting the data into a excel and e-mailing it.
Intelligent Automation on the other hand is an extension of RPA in combination with a bit of Artificial Intelligence. When RPA combines with AI then it provides the ability to achieve a more wholesome automation ecosystem when the BOTs work in cohesion with the AI engine and can do some decision making. The sophistication of the decision making however depends on the depth of the AI engine itself and the adaptive capacity of this depends on the functionality defined in the BOT.
While RPA helps users to free their work hours from doing mundane routing tasks , Intelligent Automation helps an organization to achieve Digital Transformation.
RPA is the use of robots to do specific tasks. IA incorporates RPA plus more intelligent features.
IA can, for example, recognize handwritten documents, convert it into searchable text documents and allows robots to parse text and plug it in as date into an SAP system. IA reduces further human intervention by adding an element of AI in the process.
RPA is the core functionality of automation; wherein, intelligent automation layers in cognitive ability (e.g., artificial intelligence, machine learning, etc.). Moves up the maturity from 'doing' what a human does to 'thinking/acting' like a human. For example, instead of creating templates for various types of invoices, you can leverage intelligent character recognition for a more scalable solution.
RPA is a repetitive easy straight thru process (Tasks of an activity) that necessarily has only flow - the natural flow. It doesn't handle alternate and exceptional flows. It is also purely at a transactional level; such as collecting information about a service request and confirming that the necessary information has been received and perhaps can be sent to people assigned for it. IPA on the other hand should handle the exception flows and alternate flows in addition to a normal flow completing a Process loop (Associated Activities + their connected Tasks). The flow of RPA is data to Information only; where Information can take the form of Messaging / Communications. IPA on the other hand extends to from data to information to intelligence to even Knowledge / Records in a recursive manner converging and automating the roles of both machine and human interventions.
The short answer I can give is RPA is a software robot that handles repetitive mundane tasks which frees humans to perform higher value work and analysis. The bot automates high volume lower complexity processes that are prone to human error. It will run applications the same way a person works with that software. Intelligent Automation includes RPA but goes much deeper by incorporating machine learning, NLP and deeper analytics to improve decision making logic into the equation.
RPA: automate repetitive tasks or processes, IA: automate digital document data extraction applying machine learning to OCR (optical character recognition) technologies, in a standard formtat (like invoices, purchase orders, etc). Also for automating image recognition or sentiment analysis integrating cognitive services (Watson, Azure, AWS...)
IA is a combination of technologies such as RPA AI,NLP, Intelligent OCR, computer vision...to streamline the processes from end to end.
RPA takes the robot part from human work ;however, IA will be needed to handle the cognitive part of the work to ensure business continuity and complete flow of process.
Intelligent Automation (IA)
A holistic solution for the digital transformation of operational
business processes through a convergence of technologies
and strategies (e.g. RPA, ML, BPM).
RPA (the hands) - Robotic Process Automation: automating repetitive
actions using RPA software.
ML Services (the brains) - versatile Machine Learning models
that are relatively easy to implement
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