RPA to Cognitive Automation: When Do You Make the Shift?

Timothy Joseph
Timothy Joseph | October 4, 2022

RPA to Cognitive Automation: When Do You Make the Shift?

While companies rely on robotic process automation (RPA) using computer-coded rule-based software robots to automate repetitive activities like reading emails and documents, understanding speech and analyzing language, the growing complexity of organizational processes and spread of digitization has necessitated the implementation of AI to help robots resolve inconsistencies, perform cognitive tasks and resolve uncertainties.

This is where cognitive automation comes into play.

This article will describe in full detail what cognitive automation is and how it can greatly benefit your business. But first, let’s take a deep dive into the terminology of cognitive automation to understand its application.

What Is Cognitive RPA?

Cognitive RPA, also known as Cognitive Robotic Process Automation, is a subset of RPA that uses artificial intelligence (AI) technologies to automate work processes. These artificial intelligence technologies include machine learning (ML), text analytics, and optical character recognition (OCR). The fusion of these technologies along with RPA is known as Intelligent Process Automation (Cognitive Automation). As AI and ML technologies are advancing, RPA tools are also getting better and are paving the way for cognitive RPA platforms.

Essentially, cognitive automation is a more advanced form of RPA where the robotic process can replicate human activities. Most of the functions carried out by this automation process focus on information gathering (learning), forming contextual conclusions (reasoning), and analyzing successes and failures (self-correction).

It is also important to note that cognitive RPA has advanced process automation even without structured information. The information may come from things such as documents, emails, letters, voice documents, and so on. It is so advanced that it can even process data without the need for human intervention. In short, with AI, RPA robots can help with real-life problem solving and decision-making processes in the following ways:

  • Predictive Outcomes: AI-enabled robots can apply machine learning models for tasks like inventory forecasting, property valuation and loan default predictions.
  • Unstructured Data: AI integration can help robots read ‘messy’ data to extract invoices, route emails, and translate speech to text.
  • Variable Processes: AI powered robots can work on variable processes like language translation and resume matching.

These are just some of the things that traditional RPA can’t do as traditional RPA requires structured data. Simple-rule-based automation is outclassed by cognitive RPA.

It’s no wonder that cognitive automation is changing the world of businesses. Here are the following ways in which businesses use cognitive RPA.

  • Invoice Processing

    Cognitive automation is a great tool to set up automated workflows for invoice processing and vendor payments automatically, as it not only helps prevent errors that would come from human intervention but also reduces cycle time.

  • Payroll Processing

    Payroll processing is a hefty task that a lot of businesses have to do every month. If, in the worst-case scenario, it is not done correctly, these businesses have to suffer the consequences of delayed payments and employee dissatisfaction.

    By implementing cognitive automation, businesses can reduce the risk of these consequences by not only being able to do payroll processing but also avoid delays in payment and inaccurate employee data.


Cognitive Automation vs RPA: What’s the Difference?

A lot of businesses nowadays want automation in their business process. There are two popular forms of automation they have to choose from, which are Robot Process Automation (RPA) and cognitive automation.

However, it is easy for one to mistake one for the other and it might not be what they are looking for. The following are the differences to help you differentiate the two:

  • Functionality: Cognitive automation can solve a lot more complex situations as compared to RPA. This is thanks to cognitive automation’s AI and ML. It is able to do more than just repetitive tasks.
  • Use in Technology: Cognitive automation requires a lot of coding while RPA does not. RPA is more about configuring and deploying certain frameworks in order to function while cognitive RPA uses advanced technology to make complex decisions.
  • Analytical Usage: Cognitive automation includes advanced analytical usage while RPA does not. RPA focuses on statistics of the tasks performed, basic analytics, and only works on a small set of commands. Cognitive automation, on the other hand, is able to perform complex analytics. It is able to do tasks such as finding the issue and resolving the issue.
  • Processing Logic: Since no coding is involved in RPA, the way it is able to process data is very simple. It is not capable of handling problems and human intervention may be needed. Cognitive automation, however, is able to replicate human behavior. This is due to the integration of AI and ML capabilities where it tries to find the root issue and solve it. There are cases where human resolution may still be needed but it is able to learn how a human was able to resolve the issue.
  • Tools: There are numerous tools that are available in the market for both RPA and cognitive automation. For RPA, Blue Prism, Inflectra Rapise, UiPath, and IBM Automation Anywhere are the popular choices. For cognitive automation, Digitate Ignio, Moogsoft, and Automation Edge are the most used tools.

If you want to learn more about how RPA works, you can check it out here.


Applications of Cognitive Automation

Cognitive automation is a great tool for businesses to not only save time and effort but also money. However, many businesses are still unaware of the advantages and methods of utilization of AI in robotic process.

The following are the different applications of cognitive RPA:

  • Monitor Health of the Application: With cognitive RPA, you are able to monitor and manage functions. This is due to the software that includes analytical suites where you can evaluate the workflow of the robot’s performance. Monitoring the health of the application is really easy as it is in one centralized console that you can access anywhere.
  • Optimize Software Testing: Cognitive RPA can help you test various scenarios by changing the values of variables. You don’t need to start or stop a running application which makes the whole process very convenient. The great thing about this is that you don’t need to go through a series of process changes either.
  • Self-Correction: Cognitive RPA is able to correct itself thanks to how it is able to make complex decisions. It starts by gathering important information, identifying the root cause of the problem, and then rectifying the problem on its own. This is really useful and convenient as human intervention is rarely required.

Scope for Application of Cognitive Automation

There are numerous scopes for the application of cognitive automation. Let’s look into them in greater details:

  • Retail

    The automation process can help you get information from customers that would update the system internally based on numerous orders, queries, and modifications. This leads to not only a reduction in human intervention but also more accurate reimbursements.

  • Finance

    The automation process can address fraud management. It is able to do this by learning from data-driven insights from customers.

  • Telecom

    Personalized customer experiences can also be created. The automation process can also give a good customer experience by improving customer response time.

  • Healthcare

    Patient experience can be transformed when proactive care is enabled. Drug development can also be enhanced by accelerating the process of drug discovery, which would generate more revenue in the healthcare sector.

  • Insurance

    Computer vision is widely used by insurance companies. This helps them read information from any screen using artificial intelligence. Auto insurance companies benefit from this computer vision to remove bias.

    Processing unstructured and structured data is also beneficial for paperwork.

Benefits of Implementing Cognitive Automation

Cognitive automation offers numerous benefits. It can greatly improve business processes and outcomes. The following are the different benefits of implementing cognitive RPA into your business:

  • Discover Untapped Value

    The shift from RPA to cognitive automation unlocks significant value for any business. Due to how complex cognitive RPA is, the possibilities are endless.

  • Streamline IT Operations

    While the hype has been around the business process, it can also greatly enhance IT operations. IT personnel can authorize robots enabled by cognitive automation to take care of simple and complex tasks, while they can focus on projects that require critical thinking.

  • Automate Decision-Making

    Unstructured data is handled more efficiently through the use of cognitive RPA. What this means is that higher-value activities can be executed automatically. This is thanks to AI and how it can improve over time.

  • Increase the Value of Automation

    Automation is a lot more valued in cognitive RPA due to how well it functions. You can reduce the cases in which your automation process gets stuck while trying to solve various situations.

  • Improve CX and Operations

    Cognitive automation can help improve CX by understanding and drawing conclusions from conversation-driven experiences. It is also able to improve operations by utilizing bots and AI.


Making the Shift

When you’re considering the digital transformation of your business, you need to consider a couple of things such as your business goals, your tech stack, and budget. However, instead of incorporating cognitive automation directly by leapfrogging traditional RPA might not be a very good idea, as businesses should have a long term strategy to maximize ROI.

If you’re looking to transition but don’t know how, then we at QASource can help you. You can visit our page for more info here.


This publication is for informational purposes only, and nothing contained in it should be considered legal advice. We expressly disclaim any warranty or responsibility for damages arising out of this information and encourage you to consult with legal counsel regarding your specific needs. We do not undertake any duty to update previously posted materials.