Process automation is crucial for successful digital transformation. It helps businesses go digital and facilitates big data processing. So far, robotic process automation has successfully automated repetitive tasks, freeing time for employees to allocate their effort to more nuanced and sophisticated duties. With the rise of cognitive robotics process automation and more and more agencies specializing in artificial intelligence, organizations can automate much more complex tasks that use unstructured data and require human intelligence.
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What is Cognitive Robotics Process Automation?
Cognitive robotics process automation (CRPA) is a solution or a tool that uses Text Analytics, Machine Learning, Natural Language Processing, and other AI-based technologies to understand complex processes and adapt to different requirements and needs.
Since these tools derive their intelligence and cognition from the abovementioned AI tech and software development, they drive analytics-based decisions and efficiently undertake process accuracy and speed, along with automation.
CRPA solutions can read and analyze structured and unstructured databases to extract actionable information and course of action. This eliminates the need for human involvement in activities that require intensive labor.
How Does Cognitive RPA Work?
As the advanced version of RPA, Cognitive RPA essentially learns and imitates human actions and processes as human workers work and execute tasks. During this, CRPA solutions:
- Acquire information and contextual rules for using it
- Utilize the context and the rules to come to conclusions and
- Self-correct by learning from failures and successes
Fundamentally, cognitive robotic process automation is an approach that consists of processes, technology, and people to achieve maximum productivity and better scalability.
The CRPA’s mechanical brain, built on AI-based technology, can adapt to evolving situations, analyze them and understand their requirements. Machine Learning and Natural Language Processing make this technology intuitive and independent.
Cognitive RPA supports the human workforce by completing their business processes. However, unlike most “traditional” RPA that cannot process things like a date in an incorrect format or missing information, CRPA can handle these situations without human intervention.
While this “traditional” RPA provides automation based on structured data, CRPA enables companies to automate their processes, including unstructured data sources such as emails, voice recordings, and scanned documents.
With this technology, businesses can automate tasks that are less based on rules and are more complex.
3 Differences Between Cognitive Process Automation and RPA
As we’ve mentioned, traditional or legacy RPA solutions are adept at executing processes but cannot make judgments or fill in the missing information. CRPA tools, with injected cognition, can overcome this shortcoming.
The most significant differences between cognitive automation and RPA are their applications' scope, processing abilities, and methodologies. Also, the benefits that businesses get from CRPA and RPA are different.
1. Application Scope
RPA can take over any rule-based task that doesn’t need cognitive thinking, performing calculations, maintaining records, and analytical skills. This technology uses structured data to perform monotonous human functions with great precision and accuracy and can be applied to most organizational activities.
For example, RPA can be used for financial processes such as:
- KYC (Know-Your-Customer verification)
- Consumer and commercial underwriting
- Loan processing etc
RPA tools help banking organizations by reducing costs, accelerating processing, and boosting productivity.
The tasks that involve a lot of data and need the cognitive capabilities of a human – such as making context-based decisions, continual learning, engaging in conversations, and understanding relationships – need cognitive RPA.
For example, CRPA gives rise to:
- Chatbots
- Automated email replies
- Computer vision and virtual desktops
- Omnichannel communication with customers
2. Processing Capabilities
Robotic process automation uses basic, rule-based technology that is simple to implement, such as workflow automation. It uses an “if-then” processing approach and doesn’t require a lot of coding.
However, CRPA is a knowledge-based approach that uses advanced tech like data mining, semantic technology, and Machine Learning to simplify complex data and improve decision-making processes.
It also uses contextual analyses to make intuitive perceptions and judgments on human conversation and define rules to find optimal solutions for any given scenario.
3. Distinguishing Benefits
Businesses that use RPA gain technological support for innovation at a relatively small cost for testing new ideas. These solutions provide more time for staff and employees to focus on complex tasks that require more cognition. This boosts the overall productivity while reducing costs by leaving tedious tasks that take a lot of time to the automation tech.
For example, repetitive and monotonous tasks are part and parcel of contact center industry workplaces. These tasks do not require complex decision-making capabilities and, as such, often use RPA to capture data and use workflows to identify a customer to provide supporting information for the agent.
Specific benefits, in this case, are that the agents do not need to access multiple systems to collect contextual information, resulting in shorter calls and better customer experience (and better experience for contact center agents).
Cognitive RPA, on the other hand, automates precise business processes and requires less data to make an impact by offering mental input to humans that work on these particular tasks.
This adds to workers’ analytical capabilities without requiring the IT or data scientists’ support. The new data that is added to the system forms the system and forms connections by itself to improve, learn and adjust.
For example, in healthcare, CRPA helps caregivers understand and predict their patients’ health more efficiently. It performs tasks of high value, such as gathering and analyzing diagnostic results and dispensing drug doses, suggesting improved outcomes for the business and the patient.
Possible Applications of Cognitive RPA
Cognitive RPA can bring notable benefits and improvements to processes in various applications.
Chatbots are a blend of RPA and cognitive abilities that improve customer service by communicating with clients via instant messaging. These AI-based chat solutions provide service levels of a live, human customer representative.
Similarly, CRPA can automate dynamic interactive voice responses and email conversations. In the case of the latter, these solutions can look for triggers that tell them it’s time to compose and send an email (like an hour or date).
Cognitive RPA can be used to monitor the application health via various software robots in the development phase. They can observe different data patterns, discover trends and use suitable models to predict application changes.
Software testing optimization is another example of a common CRPA application. Manual changes are ineffective and can compromise the QA process during frequent software changes. Cognitive RPA optimizes the test assets to maintain a dynamic test suite that self-maintains the application life-cycle throughout the entire development process.
One of the most advanced methods of putting CRPA to use is omnichannel communication. As today's customers interact with businesses via a range of channels and platforms, integrating CRPS with these touchpoints enables companies to communicate more effectively with customers and meet their demands and expectations.
Cognitive automation and AI take note of the entire customer journey. Specifically, CRPA tools enable systems to understand their customers' intent, make sense of unstructured data associated with each customer, predict their behavior, and execute their requests.
For instance, a bank’s chatbot can automate the process of opening a new bank account by providing the necessary information to the client, giving them an online form to fill and requesting the KYC documents.
Cognitive Robotics Process Automation Takeaways
CRPA is the next step in the evolution of business process automation. It relies heavily on artificial intelligence-based technology such as Machine Learning, Natural Language Processing, and Text Analytics; it provides a crucial cognitive edge to robotic process automation solutions.
These tools can improve the decision-making processes, fill in the gaps in information and data and automate tasks that until now required human touch and intelligence.
For instance, CRPA-based tools are widely used in email automation, chatbot technology, health application monitoring, omnichannel communication, and other business facets.
This technology is often powered by Node.JS (read our article on why use node.js), as well as SOW software.
Therefore, cognitive robotic process automation can be an extension of your company’s customer service, QA team, or information technology department.
Just like the traditional RPA, it eliminates the need for numerous tasks that include constant human interaction, enabling your operations to work smoothly 24/7 and letting you focus on strategic aspects of your work that can generate new revenue streams.
Additionally, an custom software development companies can help you sift through the nitty-gritty of the cognitive robotics process.
Cognitive Robotics Process Automation FAQ
1. Is RPA a cognitive computing solution?
No, RPA (Robotic Process Automation) is not a cognitive computing solution but a technology that automates rule-based, repetitive tasks by mimicking human interactions with digital systems. While RPA can enhance process efficiency, it does not possess the cognitive capabilities to understand, learn, and interpret data like cognitive computing solutions.
Combined with the cognitive capabilities of AI technology, RPA becomes CRPA - Cognitive Robotic Process Automation.
