Automation and hyperautomation are two related concepts that concern the increasing application of technology in automating business and industrial processes. When we talk about automation, we refer to the use of technologies such as software and robotics to perform tasks or processes without direct human intervention. The ultimate purpose of this mechanism is specifically to increase efficiency, reduce errors, and free human resources from repetitive and monotonous activities. A common example of automation is business process automation, where automated software handles data management, communications, and other standardized operations.
On the other hand, when referring to hyperautomation, we mention a particular advanced form of automation that integrates technologies like artificial intelligence (AI) and robotic process automation (RPA) to create a highly automated and intelligent environment. Its goal is to radically transform the entire organization by improving operations, decision-making capabilities, and going beyond the automation of individual processes. It involves various key technologies such as AI, which allows systems to learn from data, draw conclusions, and make decisions similarly to human intelligence, by analyzing vast amounts of data. In this scenario, the aforementioned RPA technology plays an important role, as it involves the use of software to automate repetitive and regular tasks that would otherwise require human intervention. Additionally, the use of Machine Learning comes into play, a branch of AI that enables systems to improve and learn from experience and data. Lastly, there is Natural Language Processing (NLP), which allows computers to understand and interact with human language.
In general, automation and hyperautomation are revolutionizing the well-known process of advanced digitalization through the use of innovative methods, contributing mainly to simplifying various activities, reducing time and effort for workers, and increasingly meeting consumer needs.
The Role of the Pandemic in the Development of Hyperautomation
The recent health crisis has created conditions that push companies towards digital transformation through significant digitization of processes and services. The new dimension of the digital revolution has increased the demand for automation of business operations across all sectors. However, it has faced challenges in integrating the functions of various strategic approaches adopted so far. Hyperautomation has provided an effective response to the problems of automating business processes, offering comprehensive and sophisticated automation, simplifying opportunities for gaining efficiency in business processes.
Gartner mentioned “HyperAutomation” in the Strategic Technology Trends for 2020 report. The difference between automation and hyperautomation mainly lies in their historical context within the realm of technologies. Automation came into play with the onset of industrialization, whereas hyperautomation represents a different form of automation compared to conventional automation. It deals with end-to-end automation of processes and business cycles. Unlike typical automation that focuses on a single component of an organization, hyperautomation simultaneously transforms many processes, activities, and responsibilities across multiple divisions. This technology has emerged in recent years, and according to Gartner, the demand for hyperautomation will reach nearly $1.04 trillion by 2026, driven by a significant skills shortage, increasing economic pressures, and competitive barriers.
Hyperautomation combines several cutting-edge technologies to help companies identify complex business operations and automate them with precision and speed, enhancing operational efficiency, reducing processing and production times, and lowering costs to increase customer satisfaction. It extensively utilizes Machine Learning to improve workflows, productivity, and procedures before orchestrating the entire process with Robotic Process Automation (RPA) technologies. RPA techniques are adopted for automating repetitive and rule-based process areas.
The pandemic has accelerated the adoption of hyperautomation as organizations strive to navigate through the challenges posed by the crisis and embrace advanced technological solutions to optimize their operations and remain competitive in the evolving digital landscape.
Adoption Paths and Future Developments
Hyperautomation is built on a set of technologies primarily focused on automation and artificial intelligence. When combined, these technologies enhance human management capabilities, enabling faster and more efficient work processes and increasing productivity through a disciplined and business-oriented approach. In summary, hyperautomation involves the use of various tools or platforms, including artificial intelligence and machine learning, to streamline and improve productivity.
Let’s delve into the specific technologies involved:
- Process Mining: When used in conjunction with machine learning, it not only identifies process inefficiencies but also defines workflows capable of eliminating them through automation systems.
- Business Process Management: It identifies the necessary activities to define business processes, making the overall business more efficient.
- Robotic Process Automation (RPA): It automates work processes using software capable of performing repetitive tasks.
- AI/ML (Artificial Intelligence and Machine Learning): It enables systems to have a level of decision-making capability.
- Integration Platforms (iPaaS): These platforms integrate various complex and hybrid systems.
- Low-Code (LCAP) and No-Code Application Platforms are development environments that allow the creation of software applications without the need to write code from scratch. These platforms are esigned to simplify and expedite the software development process, enabling individuals with little or no coding experience to create applications using configuration modules and graphical interfaces.
