Cognitive Automation is Hotter than RPA

Cognitive Automation is Hotter than RPA

Almost everyone is aware of Robotic Process Automation (RPA) these days, and sales of RPA software for the next 5-6 years are predicted to rise at a surprising 50%+ yearly rate whereas the enterprise software budgets are growing less than 10% annually. One aspect of RPA is making heads turn around, Cognitive automation.

Currently available RPA software tools in the market all have cognitive capabilities to offer, and more than half of the enterprises implementing RPA will be making use of cognitive tools to their ends.

Cognitive RPA is automation that mimics human thinking. It is often equated with Artificial Intelligence (AI) but that is not correct, even though it uses many of the same technologies like AI, including natural language processing, machine learning, contextual awareness, pattern recognition, and context analyses. More specifically, cognitive automation refers to AI techniques applied to automating specific business processes.

Cognitive computing may be considered a marketing jargon by many, but in simple terms, it is described as the ability of computers to replicate human thought processes.

Here are some examples of what RPA with cognitive capabilities can do:

  • Process a broad variety of nonstandard invoices and extract data from them
  • Analyze unstructured data in customer support emails, figure out what customers need, and answer appropriately

Cognitive automation is picking up speed with advancements in underlying technologies and is becoming more popular day by day.

Most of the enterprises using cognitive automation initially started off with traditional RPA which automates repetitive and rule-based tasks that can be easily assigned to a software robot.

Most often, businesses find themselves restricted because traditional RPA automation can only handle structured data – the kind of data that comes from a spreadsheet or database or standardized forms, whether paper-based or electronic. The unstructured data are also known as “dark data” includes information found in emails, videos, social media posts, audio recordings, and handwritten notes.

Realistically speaking, the majority of data generated by businesses is dark or unstructured data.

Given its capabilities to work on unstructured data or semi-structured data, cognitive RPA accelerates the returns that enterprises get from RPA.

One peculiar trait of cognitive RPA is that intelligent bots learn over time and can be trained to do more and more heavy lifting working with semi-structured or unstructured data. Consequently, human workers can step out of processes and focus more on higher-value work leaving the mundane for the intelligent bots.

As cognitive RPA expands and underlying technologies advance, RPA will move from mainly automating basic operations, finance and IT tasks to taking over complex processes in compliance, legal, HR, and even the front office.

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