Cognitive Technology is a subset of Artificial Intelligence. It utilizes AI-powered technology such as Natural Language Processing, Optical Character Recognition, Machine Learning, Deeps Learning, Semantic Understanding, Emotion Recognition, and Contextual Analysis in order to make information-based decisions.

Modern technology is abundant. With all the new tech, there are also countless terminologies floating around. Some of these are used interchangeably, which sometimes causes enormous amounts of confusion.
In the midst of all this, observers of these advancements need to keep up with all the coinage, the connections between the tech and variations of the same. Even for the human brain, tracking all this information is often complicated. There are complex neurological processes that go into understanding and absorbing information, then using it to make logical decisions.
Similarly, in work-related situations, the human mind has to make connections and decisions based on the information provided to complete assigned tasks.
Keeping in mind that the human mind is the ultimate cognitive tool, we move on to discussing cognitive technology.

What is cognitive technology?

Cognitive is defined as “of, relating to, being, or involving conscious intellectual activity (such as thinking, reasoning, or remembering.” On a similar note, Cognitive Technology refers to technology that attempts to imitate human behavior, critical thinking, and logical reasoning.
It goes without saying that bots are creations made by humans and perform actions differently. Humans are naturally born with certain in-built capabilities that allow them to make decisions based on seemingly random, unstructured data. Until very recently, technology hadn’t been able to imitate this characteristic of the human mind. Robots that could think and function as humans do, only appeared in sci-fi cinema, often being called “cyborg” or “droid.” (Remember C3PO and Cyborg Nemesis?)

However, in the past decade, as Artificial Intelligence has caught the attention of developers and IT geniuses, cognitive technology has also been on the rise. It may not be as cool as a half-human, half-robot contraption, but it has a few amazing capabilities under its belt.

The USPs of Cognitive Technology –

  • Can be used for information heavy processes.
  • Can be used to separate and utilize unstructured data based on theme, tone, and emotion.
  • Becomes better as more data becomes available – it forms connections between data, learns continuously and makes adjustments along the way.
  • Is capable of extracting data from documents, audio/video files, telephonic conversations, images.
  • Can suggest multiple possibilities and predict situations based on trends and patterns.
  • Can utilize contextual information to analyze data.

With the power to replicate human behavior, the automation industry has jumped on the opportunity. Cognitive Technology is now being used to automate mundane repetitive business operations. This kind of automation is called Cognitive Automation.

Cognitive Automation vs Robotic Process Automation

Now, it is obvious for anyone who knows about RPA to wonder – These concepts sound similar.
Is this another case of the same solution having multiple names? And the simple answer is – No. While the use cases of these technologies are quite similar, there are a number of minute differences that make them suitable for different kinds of input and output.

To explain this, let us break a situation down.

The Situation – An aggrieved customer is calling the customer service executive regarding a problem they are facing.
What RPA can do – The correspondent will have to trigger bots to do specific tasks. These tasks may involve locating information from the database, sending pre-set communication to the customer, or updating customer information. The decision of what commands to trigger lies with the human.
On the other hand, what a cognitive tool can do – Analyze the information being provided using voice, text, and emotion recognition, suggest quick solutions and categorize information automatically.

In both these situations, the role of the human correspondent remains similar. The difference lies in the kind of aid being provided. While RPA will take over the repetitive tasks of filling in forms, sending mail and updating information, cognitive tools will provide suggestions to aid the correspondent in resolving issues. In some situations, cognitive tools will also decide what the best solution is and offer it to the user. This helps reduce the mental strain that employees feel.

RPA is not suitable for tasks that require decision making or prediction. It can be used to automate tasks that follow a specific set of commands. Cognitive automation can support automation by forming connections based on association/context and making logical decisions.

COGNITIVE AUTOMATIONROBOTIC PROCESS AUTOMATION 
  • Information/ knowledge based.
  • Pre-trained – no interference neede.
  • Can understand data, make logical decisions.
  • Adapts to variations and exceptions.
  • Can analyze structured and unstructured data.
  • Rule based.
  • Requires some attendance.
  • Cannot understand data or make logical decisions.
  • Cannot adapt to variations or exceptions.
  • Limited to structured data.

According to an IDC report, investment in AI-centered research is estimated to escalate to a whopping $52.2 billion by the end of 2021. Cognitive Automation promises to provide an upper hand to companies in various areas that include automation, customer management, analytics, data management, and diagnostics. Vendors such as Automation Anywhere, Blue Prism, NICE, UiPath, IBM, and Google are continuously striving to integrate cognitive technology with RPA and make the digital transformation journey simpler and bot-service more accurate.