Robotic Process Automation and Cognitive Automation

While RPA software can help an enterprise grow, there are some obstacles, such as organizational culture, technical issues and scaling. In this paper, UiPath Chief Robotics Officer Boris Krumrey delves into the ways RPA and AI can best achieve a powerful digital labor, detailing on implementation and operating challenges. You will also need a combination of driver and irons, you will need RPA tools, and you will need cognitive tools like ABBYY, and you are finally going to need the AI tools like IBM Watson or Google TensorFlow. Reaching the green represents implementing Intelligent Process Automation; the driver is RPA, the irons are the cognitive tools like Abbyy and the putter represents the AI tools like TensorFlow or IBM Watson. Guy Kirkwood, COO & Chief Evangelist at UiPath, and Neil Murphy, Regional Sales Director at ABBYY talk about enhancing RPA with OCR capabilities to widen the scope of automation.

However, initial tools for automation, which includes scripts, macros and robotic process automation (RPA) bots, focus on automating simple, repetitive processes. However, as those processes are automated with the help of more programming and better RPA tools, processes that require higher level cognitive functions are next in the line for automation. Organizations going through a digital transformation have more opportunities than ever to further automate their business processes. Let’s consider some proven robotic process automation use cases and the value that they can create for organizations operating in a difficult time. As CIOs embrace more automation tools like RPA, they should also consider utilizing cognitive automation for higher-level tasks to further improve business processes. By allocating more structured and repetitive tasks to robots, human employees are freed from the cumbersome and monotonous nature of manually processing very simple tasks.

What is RPA OCR?

While technologies have shown strong gains in terms of productivity and efficiency, “CIO was to look way beyond this,” said Tom Taulli author of The Robotic Process Automation Handbook. Cognitive automation will enable them to get more time savings and cost efficiencies from automation. “To achieve this level of automation, CIOs are realizing there’s a big difference between automating manual data entry and digitally changing how entire processes are executed,” Macciola said. Basic cognitive services are often customized, rather than designed from scratch. This makes it easier for business users to provision and customize cognitive automation that reflects their expertise and familiarity with the business.

Another benefit of cognitive automation lies in handling unstructured data more efficiently compared to traditional RPA, which works best with structured data sources. Cognitive automation can use AI to reduce the cases where automation gets stuck while encountering different types of data or different processes. For example, AI can reduce the time to recover in an IT failure by recognizing anomalies across IT systems and identifying the root cause of a problem more quickly. This can lead to big time savings for employees who can spend more time considering strategic improvements rather than clarifying and verifying documents or troubleshooting IT errors across complex cloud environments. Intelligent automation streamlines processes that were otherwise comprised of manual tasks or based on legacy systems, which can be resource-intensive, costly, and prone to human error.

What Is Cognitive Automation? A Primer

Although much of the hype around cognitive automation has focused on business processes, there are also significant benefits of cognitive automation that have to do with enhanced IT automation. Check out the below video which explains exactly how an intelligent robotic workforce extracts, analyses and interprets unstructured data at scale, while also learning from human input. Combining both attended and unattended robots in your RPA framework can unlock a significant amount of value. This seamless combination of attended and unattended bots has the capabilities to automate more tasks, more accurately and with more speed. In addition, more complex process automation requirements can be supported, in the event of a process error or exception, requiring real-time human input or intervention. Another key difference is that while traditional RPA uses structured inputs and logic, AI uses unstructured inputs and develops its own logic.

The ideal way would be to test the RPA tool to be procured against the cognitive capabilities required by the process you will automate in your company. FinTech Magazine and its entire portfolio is now an established and trusted voice on all things FinTech, engaging with a highly targeted audience of 113,000 global executives. We provide key industry players with the perfect platform to showcase their brands, develop content syndication plans, webinars, white papers, demand generation as well as a global set of events (In-Person & Virtual).

Decisions, decisions…

RPA software can handle tasks such as moving from one application to another, inputting data into multiple fields, reentering data, or copying and pasting — nearly any task that is largely driven by rules and schedules. The robot is a software worker that can do jobs such as retrieving customer profiles, supporting and ordering information from multiple enterprise systems and applications. We support disruptive ways to transform business processes through the introduction of cognitive automation within our technology. Unstructured images (documents) require OCR/ICR capabilities to extract the data. If an image has a consistent format, such as payable invoices, payment remittance, etc., then these images can be converted using OCR/ICR technologies, and the output will be readily consumable by the downstream process. If the format is inconsistent, then OCR/ICR technologies will deliver unstructured text data, which needs further processing.

• This seamless combination of attended and unattended bots has the capabilities to automate more tasks, more accurately and with more speed.
• The best RPA tools are not just tools for building automation capabilities, but for identifying and planning before the build as well as post-deployment monitoring.
• Chatbots are tasked with communicating with humans through a messaging interface, such as Facebook Messenger, WeChat, Slack or chats embedded on websites.

It’s an AI-driven RPA solution that helps you automate more business and IT processes at scale with the ease and speed of traditional RPA. He focuses on cognitive automation, artificial intelligence, RPA, and mobility. The coolest thing is that as new data is added to a cognitive system, the system can make more and more connections. This allows cognitive automation systems to keep learning unsupervised, and constantly adjusting to the new information they are being fed. Millions of companies in the world today are processing endless documents in various formats.

The COVID-19 pandemic has only expedited digital transformation efforts, fueling more investment within infrastructure to support automation. Individuals focused on low-level work will be reallocated to implement and scale these solutions as well as other higher-level tasks. Middle managers will need to shift their focus on the more human elements of their job to sustain motivation within the workforce.

This abstract delves into real-world applications, showcasing how businesses can leverage this symbiotic relationship to optimize various facets of their operations. From accelerating data processing and reducing errors to enhancing customer experiences through personalized interactions, the combined force of RPA and AI opens avenues for unparalleled business process optimization. Vendors claim that 70-80% of corporate knowledge tasks can be automated with increased cognitive capabilities. To deal with unstructured data, cognitive bots need to be capable of machine learning and natural language processing.

Banking – Processing trade finance transactions

The UIPath Robot can take the role of an automated assistant running efficiently by your side, under supervision or it can quietly and autonomously process all the high-volume work that does not require constant human intervention. You might even have noticed that some RPA software vendors — Automation Anywhere is one of them — are attempting to be more precise with their language. Rather than call our intelligent software robot (bot) product an AI-based solution, we say it is built around cognitive computing theories. And if you are planning to invest in an off-the-shelf RPA solution, scroll through our data-driven list of RPA tools and other automation solutions.

In addition, other processes which are very error prone (when executed manually) and only executed seasonally, could potentially be good process candidates for automation. Robotic process automation (RPA), also known as software robotics, uses automation technologies to mimic back-office tasks of human workers, such as extracting data, filling in forms, moving files, et cetera. It combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.

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Unstructured images (pictures) are the type of input documents where a picture needs to be interpreted to extract information. For example, an engineering diagram of a building that needs to be converted into a bill of material rapidly due to the competitive nature of the bid process. Much of the recent boom in AI can be attributed to the application of deep neural networking over the past decade. On the one hand, convolutional neural networks – a specialized application of deep neural networks – are designed specifically for taking images as input and are effective for computer vision tasks, an area where UiPath invests heavily. On the other hand, recurrent neural networks are well suited to language problems.

As the digital agenda becomes more democratized in companies and cognitive automation more systemically applied, the relationship and integration of IT and the business functions will become much more complex. Cognitive automation promises to enhance other forms of automation tooling, including RPA and low-code platforms, by infusing AI into business processes. These enhancements have the potential to open new automation use cases and enhance the performance of existing automations.

These areas include data and systems architecture, infrastructure accessibility and operational connectivity to the business. IBM Cloud Pak® for Automation provide a complete and modular set of AI-powered automation capabilities to tackle rpa cognitive automation both common and complex operational challenges. Achieve faster ROI with full-featured AI-driven robotic process automation (RPA). To learn more about what’s required of business users to set up RPA tools, read on in our blog here.

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It also suggests a way of packaging AI and automation capabilities for capturing best practices, facilitating reuse or as part of an AI service app store. IBM Consulting’s extreme automation consulting services enable enterprises to move beyond simple task automations to handling high-profile, customer-facing and revenue-producing processes with built-in adoption and scale. Leading companies automate both business and IT to free up employees to focus on what they do best. The integration of these three components creates a transformative solution that streamlines processes and simplifies workflows to ultimately improve the customer experience. The integration of these components to create a solution that powers business and technology transformation.