In case you hadn’t heard it yet: the newest buzz in IT automation is hyperautomation. At least: that’s what the researchers at Gartner call it, who even hailed this brand new automation concept as the number one strategic technology trend for 2020. Forrester and IDC refer to it, respectively, as Digital Process Automation (DPA) and Intelligent Process Automation (IPA). But never mind its name: what is all the buzz about, really?
Let’s start by defining the concept. Sticking with Gartner, we find that “hyperautomation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans.” Judging from this definition, it would seem that Gartner, like many if not most of us, has also arrived at the conclusion that “no single tool can replace humans” – not yet, that is. So for the time being – or in the short term, anyway - it is the intelligent interaction between old-fashioned human labour and the innovative support of software robots that will continue to drive business growth.
Seeing that “no single tool can replace humans”, in Gartner’s view hyperautomation logically “extends across a range of tools that can be automated” and combined, “including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making.”
What comes after RPA
Hyperautomation could also simply be defined as the combination of robotic process automation with artificial intelligence and machine learning. Organisations generally turn to RPA solutions to automate an existing manual task or process or to automate the functionality of legacy systems. But while RPA may be an integral part of hyperautomation and even sit at the centre of it, Gartner makes it quite clear that this new concept is really about what comes after RPA. The title of an in-depth Gartner report on hyperautomation speaks volumes in that respect: “Move Beyond RPA to Deliver Hyperautomation.”
With RPA software sales increasing by 63% to USD 846 million, according to Gartner, this was effectively the fastest-growing segment of the global enterprise software market in 2018 (overall, that market grew at just 13%). Moreover, Gartner sized the RPA services market in 2018 to be worth USD 4.5 billion. That same year, the research firm also predicted a total spend on RPA software amounting to USD 2.4 billion in 2022. And at the end of last year, Gartner predicted a 30% increase in the use of RPA for front-office functions (sales and customer experience) by 2023.
Admittedly, in absolute numbers today’s RPA market is still relatively small. It is maturing and consolidating at an impressive speed, though, as the overall use of RPA keeps on expanding. And hyperautomation as the next trend in IT automation is clearly expected to build on the very real success that underlies this phenomenal growth of RPA: the ease and speed of automation, as well as its proven positive impact on business operations.
Managing unstructured data
RPA solutions typically perform best when an organisation needs structured data to automate existing manual tasks or processes. As a rule-based software, RPA is indeed most effective at automating highly structured workflows, such as a fixed sequence of clicks that achieves a given purpose within an application. That RPA only addresses workflows involving structured data, whereas today the vast majority of enterprise data is unstructured, is also its fundamental limitation
With hyperautomation, AI - and machine learning in particular - slides in alongside RPA as a means to better manage those unstructured data workflows, including images, videos and even richer file formats for 3D, augmented reality (AR) and virtual reality (VR). These workflows introduce new levels of ambiguity and are less rule-based than guideline-based. Consequently, managing them requires the support of software robots that are much less robotic than today’s RPAs. And that is exactly where hyperautomation comes in.