Hyperautomation

Hyperautomation consists of increasing the automation of business processes (production chains, work flows, marketing processes, etc.) by introducing Artificial Intelligence (AI), Machine Learning (ML) and Robotic Process Automation (RPA). To a point where almost any repetitive task can be automated and it is even possible to find out which processes can be automated and to create bots to perform them.

In addition, hyperautomation is a key factor in the digital transformation as it eliminates human involvement in low-value processes and provides data that offers a level of business intelligence that was not available before. It can become a key factor in building fluid organisations capable of adapting rapidly to change.

Why is hyperautomation important? 

Hyperautomation refers to a superpower automation process combining several key elements: the power of artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and optical character recognition (OCR). At its core, hyperautomation begins with RPA and adds a range of advanced technologies to achieve end-to-end automation through advanced tools and analytics like AI, machine learning, and business process management systems (BPMS). 

In other words, hyperautomation scales on automation and amplifies its capabilities, building a process that is constantly advancing and improving through data. By adding intelligence to automation, this combination offers the horsepower and flexibility to automate the toughest processes – including undocumented operations that depend on unstructured information.

Independent of an organization’s infrastructure and repetitive labor, automation robots backed by AI and ML can still maneuver unstructured data inputs and make nuanced decisions. This enables enterprises to address customer expectations quickly, fulfill business goals, improve productivity, and boost efficiency. 

For example, pure RPA bots are limited to reading standardized and digitized invoices and documents. On the other hand, when OCR and NLP are added to RPA,  hyperautomated robots can perform tedious yet intuitive tasks such as sales reports, contracts, and reading invoices, emails, or official documents in various formats from different vendors. They can also listen, read, and engage in conversations to help respond and identify opportunities at record speed. 

The key points of hyperautomation

Hyperautomation is not based on one single technology but on integrating a number of them, including:

• Robotic Process Automation - Robotic process automation makes it possible to configure software that allows robots to perform repetitive, structured tasks in digital systems.
• Machine Learning - Machine Learning is the technology that uses algorithms to teach computers to perform complex tasks by themselves without the need for additional programming by human beings.
• Artificial Intelligence - The purpose of Artificial Intelligence is to create machines that are capable of making decisions and solving problems by emulating human logical thinking.
• Big Data - Big Data is a set of technologies that make it possible to store, analyse and manage huge amounts of data produced by devices in order to identify patterns and create optimal solutions.
• Cobots - Cobots are the prime example of collaborative robotics, in other words, robots that share tasks with human workers and are revolutionising production processes.
• Chatbots - Chatbots are systems based on AI, ML and Natural Language Processing (NLP) that can hold a conversation in real time with a human being using text or speech.

Advantages of hyperautomation

Hyperautomation has numerous advantages, both for the performance of a company as well as for the well-being of its workers. These include:

• The integration of disruptive technologies, such as AI, ML, RPA and NLP, into the day-to-day workings of the company, allowing it to perform processes more quickly and efficiently and reducing errors.
• Increased employee satisfaction, as they are operating in a smart working environment and do not have to waste their time on tedious tasks that add no value, and it enhances the ability of the workforce to increase productivity and competitiveness.
• Organisations can transform digitally, aligning their business processes and their investment in technology.
• Reduction in the operating costs of organisations. According to Gartner, by 2024, combining hyperautomation technologies with redesigned operating processes will cut costs by 30 %.
• Big Data and AI technology mean business information can be extracted from data and decisions made more effectively.

What are some hyperautomation use cases?

Hyperautomation's enhanced robotic intelligence capabilities enable organizations to amplify the automation of key business processes. A few use cases include:

• Healthcare: Machine learning, AI, NLP, and RPA provide immense value in improving processes in the healthcare industry. Using these tools together, hyperautomation enables organizations to save time, standardize processes, and reduce errors by automating repetitive tasks related to patient testing, medication reconciliation, patient registration, insurance verification, and more. 
• Financial services: The rise of alternative lending methods, fintechs, and challenger banks has made the financial services industry even more competitive. With hyperautomation, financial institutions can transform their operations and remain competitive by improving customer onboarding, streamlining compliance processes, and improving accuracy and speed.
• Customer service: As customer expectations and demands change, a business must find ways to adapt its operations to address customer concerns and enhance the customer experience. Integrating hyperautomation into customer service processes and systems can reduce manual tasks, sort queries, provide fast solutions, and streamline workflows.