This is a term you will hear more and more: hyper-automation. Basically, hyper-automation relates to a “conglomerate” of technologies ranging from RPA (Robotic Process Automation) to machine learning.
Robotic process automation is based on robotic digital workers. It is sometimes referred to as ‘software robotics’. It is one of the pillars of Hyper-Automation.
Hyper-Automation is a growing trend that pushes for the maximal usage of rational processes that can be automated by hardware or software robots. Think of programming an automatic test generator, the programmer being an Artificial intelligence and robots will execute the tests for some industrial process.
Humans, therefore, stay at the center of a giant automation orchestra that they rule and govern.
Therefore, how is Hyper-automation different from Regular Automation?
The term automation almost immediately evokes other terms like robotic process automation. But, hyper-automation involves a full ecosystem of technologically advanced tools and orchestrates them to create a new way of working.
It means that tasks with small added values are performed in an optimal way with automation tools, machine learning, and advanced artificial intelligence in such a way the production will require almost no human interaction.
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Architects and people involved in industrial processes in order for their businesses to stay competitive have to provide end-to-end automation …. beyond RPA by merging different but complementary technologies in order to increase business processes.
RPA is not enough: There is a lack of guidance to provide organizations with a real vision to assemble robotic process automation (RPA) with other automation tools. This damages the end-to-end process of automation, and this causes these organizations to miss out on many valuable business scenarios.
It is estimated that by 2022, 65% of commercial or public organizations that are already using robotic process automation will have to introduce artificial intelligence, including machine learning (neural networks, etc.).
RPA is able often to provide quick relief when building automation in a business. However, processes are not always that simple with a routine, repetitive, and stable scenario. They may be complex, and they almost always involve intelligent automated decision-making.
RPA therefore cannot solve such issues itself and need to be integrated into a much more complex and vast ecosystem of tools and processes: this is the real behind hyper-automation!
RPA is a technology that provides a non-invasive methodology for integration with existing systems and automation of repetitive, routine, and predictable tasks by using UI interactions that are orchestrated by special software and which emulate human interaction.
For example, RPA typically will integrate with ‘legacy’ applications by using a face design pattern and building APIs. This can involve techniques such as automated IT UIs interactions for instance.
It is non-invasive because it ‘plugs’ itself where human interaction was needed before without messing with the legacy system at all but emulating a human operator.
But as we said RPA is far too limited when it comes to complex automation tasks and can be only one of the pillars of hyper-automation.
By now, most of the customer requests received by call centers can be provided to software robotic agents via a dashboard. If an issue is escalated to a human customer service agent, then RPA can help consolidate the information so that everything is already available for supporting the customer.
Call center automation software is able to deal with tasks such as:
Here are a few examples of hyper-automation software for Call centers:
Hyper-automation in data processing can process legacy systems, often with AI+Optical character recognition. The migration from a legacy system to a newer system can be automated and therefore remove any human error.
Hyper-automation can be applied to processing claims and detecting errors or frauds in a legacy administrative processing. For example, WorkFusion’s platform can do that.
RBA is already present in the banking industry and in fintech companies in general.
The company AutomationEdge develops such systems using chatbots, NLP, and robot farms.
Other applications include:
The power and potential of hyper-automation are so great that Gartner described it as a Top 10 Technology Trend for 2020.
Independently of that, Forrester Research estimates that the global value of the RPA market will be at least $2.9 billion by 2021.
In general, Hyper-Automation is considered to be the future of automation. A very futuristic vision where robotic machines are being driven by Artificial Intelligences and repaired by other robotic machines.
Robotic process automation version 2.0 is usually referred to as RPAAI or “unassisted RPA” and this is considered to be the future generation of RPA technologies.
Because of progress in technology, companies can now afford RPAAI without engaging a considerable budget for it.
What we tried to describe with hyper-automation is a system where processes which used to be done by humans, not only factory workers, but we do well in other industries like insurance, software development, medical industry, etc. can be substituted by a combination of processes, software, tools, robotics devices, and machine learning algorithms.
There are almost no limits to such automation. This is what is defined by hyper-automation.
Of course, there are fantastic barriers and problems when considering the massive adoption of hyper-automation, some of them are obvious: what will be the role of billions of people in a world shaped by hyper-automation?
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