RPA vs. Cognitive Automation: Key Differences Explained

As organizations strive to stay ahead, they are increasingly turning to automation technologies to speed up processes, reduce human errors, enhance productivity, and more. Among the most prominent solutions are Robotic Process Automation (RPA) and Cognitive Automation. However, with these two automation approaches gaining traction, businesses often struggle to determine which one best fits their needs.

In this blog, we will explore the key differences between RPA and Cognitive Automation, providing a clear understanding of how each technology works and how it can benefit your organization. This automation technologies comparison will guide you in making an informed decision. So, let’s dive into the world of RPA vs. Cognitive Automation and uncover which solution can help your business thrive in an ever-evolving market.

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Robotic vs Cognitive: Understanding the Spectrum of Intelligent Automation

As per a research by Grand View Research, Inc., the global RPA market, by the year 2025, is estimated to cross USD 3.11 billion, while the AI market, an integral part of cognitive automation, is expected to reach USD 191 billion by the year 2024, growing at a CAGR of 37%. These rapid growth forecasts highlight the transformative potential of both RPA and cognitive automation in reshaping business operations. RPA automates repetitive tasks, improving efficiency, while cognitive automation uses AI to mimic human thinking, enabling businesses to handle complex, information-intensive processes with unmatched speed, accuracy, and consistency. Together, they represent the spectrum of intelligent automation, driving smarter, more efficient business practices.

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Two Crucial Differences between RPA and Cognitive Automation

The primary differences between RPA and cognitive automation lie in their application scope, underlying technologies, methodologies, and processing capabilities. Here’s an overview of automation technologies comparison based on these two factors:

1. Different Underlying Technologies, Methodologies, and Processing Capabilities

RPA operates with basic technologies like macro scripts and workflow automation, making it simple to implement. It follows a rule-based approach, using minimal coding with an "if-then" structure to execute tasks efficiently.

Cognitive automation, by contrast, is based on a knowledge-driven approach, utilizing more complex technologies such as natural language processing (NLP), text analytics, data mining, semantic technology, and machine learning. These technologies allow cognitive automation to process complex data and assist in making informed business decisions by applying contextual analysis. This approach enables more intuitive judgment and solutions tailored to specific situations, mimicking human cognitive abilities.

‍2. Diverse Scope of Application

RPA is designed to handle structured data and automate repetitive, rule-based tasks that don’t require cognitive thinking or complex analysis. Tasks like answering queries, performing calculations, and managing records or transactions are ideal for RPA, which can streamline up to 60% of an enterprise's activities.

In industries like banking and finance, RPA can efficiently manage processes such as retail branch operations, underwriting, loan processing, anti-money laundering efforts, and KYC. This automation helps organizations reduce costs, increase productivity, and speed up back-office functions, giving them a competitive edge.

However, RPA falls short when tasks involve large data sets or require human cognitive abilities such as continuous learning, decision-making based on context, understanding intricate relationships, or engaging in conversations. This is where cognitive automation excels. Cognitive automation employs advanced AI techniques to perform non-routine tasks, analyzing unstructured data to support human decision-making and improve performance.

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Distinguishing Benefits: RPA vs. Cognitive Automation

RPA

RPA enables businesses to innovate without heavy costs by automating routine tasks, freeing employees to focus on more complex activities. It can be quickly implemented, boosting productivity and reducing costs and attrition by handling repetitive work over extended periods.

In the contact center industry, where repetitive tasks are common, RPA automates data capture, integrates workflows, and provides agents with all necessary information on a single screen, eliminating the need to access multiple systems. This leads to shorter call durations and a better experience for both customers and agents.

Cognitive Automation

Cognitive automation, on the other hand, is pre-trained for specific tasks, requiring minimal data to start delivering results. It enhances human decision-making with cognitive insights and can be used directly by business users without IT or data science support. It adapts and learns from new data, making it operational within weeks.

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Final View: RPA or Cognitive Automation?

In a nutshell, the ideal approach isn't about choosing one over the other. Since RPA and cognitive automation represent two ends of the same spectrum, organizations often begin with RPA to manage high volumes and gradually progress to cognitive automation to tackle both volume and complexity. Beyond cost considerations, factors such as the type of data also play a crucial role in determining the right blend of RPA and cognitive automation for your business.

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Get in touch with us for expert advice on implementing RPA or Cognitive Automation tailored to your business.

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