Almost everyone has heard of RPA, and nearly everyone is doing it. Sales of RPA software between 2016 and 2022 is predicted to rise at an astounding 57% yearly rate at a time when enterprise software budgets are growing at just 4.1% annually.
But one aspect of RPA is raising corporate eyebrows even higher.
Almost half of enterprises implementing RPA in the next six months will be doing so with cognitive capabilities.
Cognitive RPA is automation that works by imitating the way humans think. It is often used synonymously with artificial intelligence (AI), but that is strictly not correct, even though it uses many of the same technology building blocks as AI, including natural language processing, machine learning, deep learning, and context analyses. (For a more complete definition of cognitive AI, see my blog “What is Cognitive Automation? A Primer.”)
Cognitive computing is considered a marketing jargon by many, but in layman terms it is used to define the ability of computers to replicate or stimulate human thought processes. The processes behind cognitive computing may make use of the same principles as AI, including neural networks, machine learning, contextual awareness, sentimental analysis, and natural language processing.
Some examples of what RPA plus cognitive capabilities can do:
- Process a broad variety of nonstandard purchase orders (P.O.s) and extract data from them to feed into a billing system
- Turn balance sheets and income statement documents into standardized machine readable excel sheets
- Analyze unstructured data in customer support emails, figure out what customers need, and answer immediately or escalate to a human
Why is cognitive becoming so popular?
Most of the enterprises deploying cognitive automation started with traditional RPA, which automates simple, repetitive tasks that can be easily replicated by instructing a software robot (bot) to copy keystrokes or follow a set of clear-cut rules.
But often, businesses find themselves limited because traditional RPA can only handle structured data—the kind of data that comes from a spreadsheet or database or standardized forms, whether paper-based or electronic. And so much corporate data is non-structured. It’s also called “dark data,” because it is largely ignored by companies. But it includes important information like that found in emails, videos, social media, audio recordings of meetings, even handwritten notes.
According to IDC, nearly 80% of data generated or collected by businesses is dark data.
Because of this capability to process unstructured data, cognitive RPA actually accelerates the already-significant returns that enterprises get from RPA—achieving ROIs of up to 300% in months, according to McKinsey.
And what’s especially attractive about cognitive RPA is that the intelligent bots learn over time. As you train the bots to do more and more heavy lifting, humans can begin to step out of processes altogether, giving them time to focus on higher-value work. As cognitive RPA expands, 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.