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Intelligent Automation (IA) vs. Robotic Process Automation (RPA)

Nearly every business today relies on some form of automation or plans to soon invest in automating parts of their business processes. In a highly competitive world where disruptive newcomers can turn the tables on established industry giants, maintaining an edge in both cost-effectiveness and real-world productivity is essential to long-term success. However, uncertainty often remains among key stakeholders about where and how to automate.

With terms such as “robotic process automation,” “intelligent process automation,” and even “hyperautomation” buzzing around in boardrooms, understanding the difference—and the different impacts of new technology—isn’t always easy. Regarding IA and RPA, what are the most important differences to know and where should your business invest for the greatest chances of success?

In this blog, we’ll look at the following topics:

  • RPA and IA: The Fundamental Difference
  • What is Intelligent Process Automation?
  • Why Do Businesses Choose RPA or IA?
  • Is RPA a Necessary Element of Intelligent Automation?
  • Where Will Intelligent Process Technology Have the Biggest Impact?

RPA and IA: The Fundamental Difference

Robotic Process Automation (RPA) vs. Intelligent Process Automation (IPA)

When examining the matter of intelligent automation vs. RPA, beginning with a definition of the latter is the easiest way to differentiate the two. Robotic process automation is a strictly rules-based form of automation software that aims to speed up common tasks and reduce human error in business processes. Logging into a computer system and retrieving or creating a database record based on a triggering event is a typical example of an RPA task.

RPA works best in structured data workflows where the steps never change and exceptions are rare. Otherwise, bots break down and cannot complete their process without human intervention. Most often, businesses who deploy basic RPA do so in pursuit of “quick wins”—cost or time savings that are relatively easy to achieve and will produce the most significant impacts for the business in the short term.

While RPA has its use cases, it also has its drawbacks, especially with scalability. While basic RPA can be an important “ground floor” starting point for some businesses, it is often mistaken for a long-term solution. In reality, this is where intelligent process automation and robotic process automation diverge.

What is Intelligent Process Automation?

IPA goes beyond the basics of RPA. By incorporating machine intelligence in the form of machine learning and AI technologies, IPA evolves the functionality of RPA to become something much greater. For tasks that involve working with unstructured data, changing processes, or shifting requirements, IPA offers software that “learns” and adapts to be better at its purpose. An RPA robot can’t do that and instead requires frequent maintenance and intervention.

IPA isn’t one type of application, either—it is many different AI/ML-enabled technologies under one umbrella. Some of the key types of intelligent process technology include tools such as:

  • Natural language processing, an ML technology that parses and interprets text or input, such as a chatbot that reads user input and provides support solutions. Sentiment analysis, a subset of NLP, helps businesses understand user attitudes.
  • Optical character recognition that learns and improves based on repeated input, taking its data and digitizing it intelligently.
  • Predictive technologies that analyze large business data sets and event logs to make valuable predictions about future events.

Repetitive tasks may prove suitable for RPA, but intelligent automation goes further and does more. It mimics the impact of human intelligence on business processes, reducing the need for personal employee intervention even as processes reach large, complex scales. Intelligent RPA can even have “self-healing” capabilities, detecting error states and handling exceptions seamlessly behind the scenes.

Why Do Businesses Choose RPA or IA?

Why are so many companies making the move today to start investing heavily in these tools? Overhauling business processes to include new technology can be a time-consuming project that requires the involvement of employees at many different levels of the company. With the growing accessibility of AI-powered tools, some of the biggest benefits include:

  • Improvements in cost-effectiveness and reduction of waste. IPA generates significantly greater cost savings than RPA alone, leading to longer-term bottom-line benefits.
  • Easier regulatory compliance and associated cost reductions. Many businesses, especially in health and finance, face serious cost burdens due to the complexity of compliance actions. IPA can play a critical role in this area.
  • Enhanced employee job satisfaction and a valuable redirection of skilled labor. With less time spent on repetitive tasks and more time to focus on making valuable organizational contributions, employee morale can improve.

A robust set of tools is necessary to achieve effective IPA. Process automation is a complex undertaking, but intelligent software that incorporates RPA and its more advanced counterparts lets your engineers find the best applications. The Kofax Intelligent Automation Platform unifies a wide swath of technologies under one umbrella, letting businesses leverage everything from basic rules-based RPA where necessary to document intelligence with embedded natural language processing and beyond.

Go beyond the day-to-day business strategy and embrace big picture thinking using automation to carve out a bigger competitive edge for your company. Learn more about what this package holds for today’s innovators.

Where Will Intelligent Process Technology Have the Biggest Impact?

When considering machine learning versus robotic process automation, which solutions currently have the most significant impacts on different industries? As more major players have recognized the limitations inherent to rule-based RPA, more investment has flowed into intelligent technologies. Today, you’ll find AI and machine learning shaping and reshaping key industries such as:

  • The energy sector, especially for oil and gas businesses, deals with highly complex data often in flux.
  • The world of finance, where IPA helps to identify opportunities for improved profit, deliver exceptional front-end experiences for customers and assist in anti-money laundering compliance.
  • Healthcare, where IPA and document intelligence tools combine to make paperwork handling easier, more secure and more reliable while streamlining many patient-related hospital workflows.

Innovative applications for intelligent process automation also already exist for retail businesses, manufacturers, insurers, builders and many others.

The Future of Business Automation

Ultimately, the matter facing businesses today isn’t exactly a head-to-head battle in terms of robotic process automation vs. intelligent automation. Instead, the key is to understand that a spectrum of automation exists. Remaining at the starting line, operating only purely rules-based RPA, leaves an incredible array of opportunities to improve outcomes both internally and externally. Going forward, the “hyperautomation” of processes with a variety of tools will be vital for remaining competitive.

In some industries, it already is. Choosing a platform that allows your business to move towards IPA and process automation leveraging cutting-edge machine learning and AI means taking a fundamental step towards the future of doing business. Discover today how to go beyond achieving basic savings with intelligent automation that paves the road toward better ways of doing business.

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