WHAT IS HYPER AUTOMATION?
Hyper automation is the concept of automating everything within an entire organization that can be automated. Organizations that use hyper-automation seek to automate as many business processes as possible through the use of robotic process automation (RPA), artificial intelligence (AI), and other technologies.
As it removes human involvement from low-value processes and produces data that offers a level of business intelligence that was previously unavailable, hyper-automation is a key component of digital transformation. It can play a significant role in creating flexible organizations that can change quickly.
HOW DOES IT WORK?
According to Gartner, RPA is the core that enables hyper automation technology when it is enhanced by AI and ML. Power and flexibility can be added in places where they were previously impractical by combining these technologies. As a result, tasks that were previously impossible to automate can now be done so that human capabilities can be concentrated on activities that have a higher value, like making decisions, interpreting data, and exercising critical thinking.
There are many different hyper-automation platforms that can be added on top of the technologies that businesses already have. RPA is the primary platform, as has already been mentioned, but there are also information engines, intelligent business process management suites (iBPMS), and integration platforms as a service (iPaaS). A digital twin of an organisation, or DTO, can be produced with the aid of hyper-automation. A DTO is a virtual representation of a product or workflow that can simulate how processes interact and demonstrate where value is produced in real-time.
THE ESSENTIAL ELEMENTS OF HYPER-AUTOMATION
Hyper automation is based on integrating various technologies, such as the following:
Automating Process Robotically
Robotic process automation makes it possible to set up the software so that robots can work in digital systems to complete repetitive, organized tasks.
Learning Machines
Machine learning is a field of computer science that employs algorithms to train computers to carry out challenging tasks without further human programming.
Machine intelligence
The goal of artificial intelligence is to build machines that can think logically like humans do when making decisions and solving problems.
Big Data
Big Data is a collection of technologies that enables the storage, analysis, and management of enormous amounts of data generated by devices in order to spot patterns and develop the best possible solutions.
Cobots
Cobots, or robots that collaborate with humans on tasks and are revolutionizing manufacturing processes, are the best example of collaborative robotics.
Chatbots
Artificial intelligence (AI), machine learning (ML), and natural language processing (NLP)-based systems called chatbots can communicate with humans in real time via text or voice.
BENEFITS OF HYPERAUTOMATION
A company’s performance as well as the welfare of its employees can benefit greatly from hyper automation. These consist of:
the incorporation of disruptive technologies like AI, ML, RPA, and NLP into daily operations of the business to improve process performance, cut down on errors, and increase efficiency.
Increased employee satisfaction because they work in a smart environment and don’t have to waste their time on pointless tasks, and it improves the workforce’s capacity to boost productivity and competitiveness.
By coordinating their business processes and technology investments, organizations can undergo digital transformation.
Reduction of an organization’s operating expenses. By 2024, hyperautomation technologies and new operating procedures will reduce costs by 30%, predicts Gartner.
Big Data and AI technology allow for the more efficient extraction of business-related information from data and the making of decisions.
