What Is Hyperautomation and How Does It Work?

What Is Hyperautomation and How Does It Work

COVID-19 accelerated digital transformation by causing worldwide workplace disruption. The massive shift to remote work brought forth the necessity of automating manual processes, and businesses implement robotic process automation (RPA) across different industries. Soon, these organizations discover the possibilities and then deploy many automation initiatives. The outcomes were impressive, but organizational leaders realized RPA is not enough, They need to do more by integrating them with other tools and technologies. Furthermore, the advantages of coordinating these individual RPA initiatives also become apparent to business leaders. RPA solution providers also came up with new tools and solutions to support this approach and the new framework: hyper automation.

What is hyperautomation?

Hyperautomation is a framework and a collection of sophisticated technologies for expanding corporate automation. Its ultimate purpose is to establish a mechanism for automating the entire enterprise automation system with the following advanced technologies.

  • The tools for finding and prioritizing automation possibilities, such as process mining and task mining, are used in hyper automation for process and task discoveries.
  • Automation development tools that reduce the time and expense of creating automation. These consist of RPA, no-code or low-code development tools, integration platform as a service tool, and workload automation tools.
  • Intelligent business process management, decision management, and business rules management are examples of business logic technologies that make it simpler to adapt and reuse automation.
  • AI and machine learning technologies extend the automation capabilities. Natural language processing (NLP), optical character recognition (OCR), machine vision, virtual agents, and chatbots are among the tools that you can integrate with RPA.

Gartner coined the term hyper automation in 2019. The idea stems from the realization that robotic process automation (RPA) is difficult to scale at the business level and is confines to certain types of automation it can perform. RPA is a relatively new and immensely popular way of automating computer-based operations. Hyperautomation is a framework that enables the strategic deployment of multiple automation technologies separately or in tandem, augmented by AI and ML.

As a result, hyperautomation requires a methodical approach to automation. A hyper automation technique entails determining which tasks to automate by selecting the proper automation technologies. It focuses on increasing agility through the reuse of automated processes and expanding its capabilities with different types of AI and ML technologies. Hyperautomation activities are frequently managed through a center of excellence that aids in the advancement of automation efforts.

The goal of hyper automation is to capitalize on the data gathered and created by computerized processes to cut costs, increase productivity, and achieve efficiency. As a result, organizations can use such data to make more informed and timely business choices.

How does hyperautomation function?

Rather than referring to a single, out-of-the-box technology or solution, hyperautomation focuses on increasing intelligence. It also refers to a systems-based approach to extending automation activities. The approach emphasizes the significance of striking the correct balance between automating manual tasks and improving complicated processes. It also reduces cycles and steps in implementing and running automation.

A critical challenge is determining who should be in charge of automation and how to accomplish it. Front-line employees are in a better position to identify tedious tasks that are ideal for automation. But business process professionals are in a better position to discover automation possibilities that involve a large number of employees.

AI and ML

Automations may interact with the world in new ways courtesy of AI and machine learning components. OCR enables automation to process text or numbers from paper or PDF documents. NLP can extract and arrange information from documents. The actions include detecting which company issued the invoice and why, and automatically entering this information into the accounting system.

A hyperautomation platform can be built directly on top of existing technology. RPA is the gateway to hyperautomation. So, all leading RPA solution providers are now adding support for process mining, digital worker analytics, and AI integration.


Gartner has proposed the concept of an organization’s digital twin (DTO). This is a simulated representation of how business processes function. So, using the correct mix of process mining and task mining, organizations can build and update the process representation. Process mining is the process of constructing a representation of process flows by analyzing enterprise software logs. Further, this can be done from business management software like CRM and ERP systems. Task mining creates process views that span many applications by using machine vision software that runs on user’s desktop.

Task mining and process mining tools can generate the DTO automatically. This allows businesses to see how functions, processes, and key performance indicators interact to drive value to the business. The DTO can assist organizations in determining how new automation can bring more value. It also creates new opportunities, or identifies possible bottlenecks that needs resolution.

Automation platforms

Furthermore, various low-code automation platforms, such as low-code development tools, integration platform as a service (iPaaS), and business process management suites (BPMS/intelligent BPMS), are introducing support for other hyperautomation technology components.

Wrap Up

Hyperautomation is already here, and it is among the top strategic technologies in the Gartner forecast. Multiple RPA solution providers and vendors have introduced various process and task mining tools and different AI integration capabilities for maximizing the potential of RPA to drive more value for your business. But it is necessary to find and employ the right tools and technologies that can complement the process, people, operation, and most importantly, your organization, satisfying the business need to successfully implement hyperautomation.

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