Heraclitus, a Greek philosopher and pioneer of wisdom, may have uttered the words: “The only thing that is constant is change”, over 2 500 years ago but the statement is especially true today. In a world defined by digital innovation and digital disruption, it feels like everything is changing, all the time.
Which is exactly what this blog post is all about. Just a few weeks ago, we unpacked everything you need to know about robotic process automation or RPA. And today we’re highlighting the next big trend in this space – intelligent process automation (IPA).
Set to reach a market value $ 13.75 billion by 2027, McKinsey describes IPA this emerging set of technologies as something that “takes the robot out of the human” by mimicking tasks carried out by people. In doing so, IPA learns to undertake these activities even better over time. It is the collection of technologies that can be used to automate and integrate digital processes. It isn’t taking the place of RPA. In fact, RPA is actually a part of IPA.
Some of these different technologies that come together under the intelligent process automation umbrella include.
Robotic process automation: A software-based solution that automates manual, rote tasks typically assigned to human employees sitting behind computers
Smart workflows: This process-management software integrates tasks performed by groups of humans and machines. Smart workflows make it possible to initiate and track the status of processes in real time.
Machine learning/advanced analytics: These algorithms identify patterns in structured data, through “supervised” and “unsupervised” learning. The algorithms learn from data sets before making predictions based on these inputs.
Natural-language generation (NLG): This software process that generates language from non-language inputs. It is the technology computers use to communicate with humans in a way that they understand.
Cognitive agents: A combination of machine learning and natural-language generation to create a totally virtual workforce. These “agents” can execute tasks, communicate, learn and even make decisions.
What does this all look like in action?
McKinsey offers the following example. In the insurance space, when a client makes a claim, the process typically sees a human claims processor conducting a search and pulling information from various different systems. “With Intelligent Process Automation, robots can replace manual clicks (RPA), interpret text-heavy communications (NLG), make rule-based decisions that don’t have to be pre-programmed (machine learning), offer customers suggestions (cognitive agents), and provide real-time tracking of handoffs between systems and people (smart workflows).”
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