Robotic process automation (RPA) has taken great leaps to improve accuracy, speed, and precision for repetitive tasks.
More and more organizations are incorporating robotic processes to speed up their time-consuming, iterative processes.
RPA technology, however, is limited to relatively simple, manual actions. RPA tools have proven to deliver output in a short time, but processes can become increasingly complex.
This has spurred new growth in RPA tools by incorporating intelligent processes.
Cognitive robotic process automation (CRPA or cognitive RPA) combines existing robotic software with the benefits of artificial intelligence (AI).
The offspring of this marriage is a hybrid tool that can perform more intelligent and complex tasks than simple data entries.
People expect automation tools not only to complete a task quickly but also to optimize the process through improved efficiency.
Businesses are starting to turn to cognitive RPA to meet their rising demands.
In a recent report, IT Technology News24 predicted that there will be a staggering 40% compound annual growth rate for the cognitive RPA market from 2019 to 2027.
This growth is expected to make the cognitive RPA market worth $150 billion globally by the end of 2027.
Cognitive RPA shows clear potential to reshape the automation landscape. In this article, we’ll explore three benefits that highlight why cognitive RPA could be right for your business.
3 Ways Cognitive RPA Tools Can Benefit Your Business
- RPA tools use AI technology to understand complex tasks
- Robot process automation adapts to different situations
- RPA tools analyze unstructured data to suggest insights
1. RPA Tools Use AI Technology to Understand Complex Tasks
As we mentioned before, legacy RPA tools are great at execution, but terrible at making judgments. That’s where cognitive RPA comes in.
Cognitive RPA tools are capable of understanding the complexities of a process thanks to their ability to sift through structured and unstructured databases.
This allows them to make judgment calls independently, which limits the need for human intervention for labor-intensive activities.
Cognitive RPA derives its intelligence from the core features of key AI technologies, including:
- Natural language processing (NLP)
- Optical character recognition (OCR)
- Machine learning
These characteristics help cognitive RPA tools make sense of volumes of data, allowing them to extract actionable information.
Whereas RPA is limited to mimicking human actions, increasingly intelligent automation can effectively augment quantitative human judgment to gain new insights.
Cognitive automation can even help with predictive decision making, as seen with Amazon Echo and Alexa.
2. Robot Process Automation Adapts to Different Situations
In addition to undertaking the three key responsibilities of automation, accuracy, and speed, a cognitive RPA tool can drive analytics-based decisions.
Simple RPA tools are unable to perform actions that are beyond the scope of their programmed regulations. But cognitive RPA tools use machine learning to gain a more informed perspective.
You can think of a cognitive RPA tool as a mechanical “brain” that can both direct and follow. It can analyze a situation, understand the current state, and adapt to evolving scenarios.
They take a holistic approach that accounts for technology, processes, and people to yield higher efficiency, better productivity, and increased scalability.
Having said that, cognitive RPA is meant to augment the human workforce, not replace it. After all, even the most sophisticated AI has its limits.
Cognitive computing is able to take on more complex tasks, but the field is still emerging when it comes to fully autonomous operations, effective commuting, and more.
At the end of the day, creative decisions should still fall on an expert’s shoulders.
3. RPA Tools Analyze Unstructured Data to Suggest Insights
Just as RPA tools eliminate the need for humans to perform mechanized, repetitive tasks for long hours, cognitive RPA takes things a step further.
They’ll still be accountable for repetitive, lengthy, and time-consuming activities. But the activities will require some level of intelligence and understanding of the tool’s part for successful completion.
These activities are primarily data-driven and rely on cognitive RPA’s analytic expertise.
Unlike RPA tools that can only use programmed, structured data, cognitive automation can leverage unstructured data to figure out probable outcomes.
Cognitive RPA is finding practical applications across various industries and organizations. It can effectively take over activities such as:
- Data entry tasks for major enterprise planning systems
- Juggling between multiple screens to perform a complex task such as billings and payments
- Reading and replying to an email based on the tone and context
- Verify and validate user credentials for loan processing or other financial transactions
As the market matures, businesses can expect even more use cases to emerge.
Cognitive RPA Is the Future of Automation
Automation can be a great value-driver but only when implemented effectively. By incorporating AI features into RPA technology, the resulting tools show promising results.
They’re able to understand more complex tasks, adapt to dynamic situations, and predict outcomes based on unstructured data.
Businesses should consider investing in cognitive RPA as it matures to help scale their operations.