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RPA and AI: How do They Work Together

RPA and AI: How do They Work Together

Ryan Spurlock

Over the last few years, Robotic Process Automation (RPA) and Artificial Intelligence (AI) have helped organizations across industries reduce operating costs significantly and enhance business efficiency and customer experience. Although both technologies can deliver significant benefits on their own, when used together, they have to power to deliver innovative and transformative business solutions that enhance productivity and efficiency, reduce operational risks, and improve customer experiences. In this blog, we explore both technologies and list down a few sample use cases where AI can be used along with RPA to deliver substantial benefits to businesses.

What is RPA?

Robotic Process Automation, also known as Software Robotics, is a technology that allows a developer to create computer software, or a “bot,” to emulate the actions of a human, integrating digital systems while executing a business process. These bots can use a user interface to capture data and manipulate applications just like humans do. They trigger responses, interpret results, and communicate with other systems to perform a variety of repetitive tasks, never needing rest and making zero mistakes. If you want to learn a little more about RPA, read our article ‘What Is RPA? – How It Works And Why It Needs To Be A Part Of Your Organization’.

AI and RPA

Artificial Intelligence (AI) is the ability of a machine to display human-like cognitive capabilities such as reasoning, learning, planning, and creativity. AI enables technical systems to perceive their environment, solve problems, respond intelligently to triggers, and act accordingly to achieve specific goals. It can receive input from various sources, either externally or through sensors such as a camera or other device. This input is processed, and it generates a response. To a certain degree, AI systems can adapt or change their behavior by analyzing the effects of previous actions and working autonomously.

A few common examples of AI in the workplace are:

  • Machine Learning
  • Document Understanding
  • AI Computer Vision
  • Chatbots
  • Process Mining

Intelligent Process Automation

When RPA and AI combine, they form Intelligent Process Automation (IPA). IPA encompasses 4 core technologies– Robotic Process Automation, Artificial Intelligence (AI), Machine Learning, and Natural Language Processing (NLP) to create smart business processes and workflows that think, learn, and adapt on their own. At its core, it is a suite of business-process improvements and next-generation tools that remove repetitive, replicable, and routine tasks, all while radically improving customer journeys by simplifying interactions and speeding up processes.

By applying Intelligent Process Automation to enterprise operations, companies can increase efficiencies and gain new capabilities beyond human abilities—such as processing millions of documents and applications a day, spotting and resolving issues within each, and making improvement recommendations. In addition, IPA can yield unique, personalized customer interactions, leading to unparalleled customer experience and satisfaction.

Intelligent Process Automation in Action

IPA possesses the cognitive ability to work with processes that contain unstructured data, making it a useful technology to tackle various use cases. By using transfer learning, IPA leverages knowledge gained from modeled tasks to solve other related tasks. Let us look at five use cases where intelligent process automation can be implemented:

  1. Invoice Processing Automation

    Automating the processing of invoices is an exercise that presents challenges to virtually all large companies. They typically receive invoices from various vendors, which means that most of these invoices almost always contain unstructured content and are of various formats. Unfortunately, Regex or other rule-based tools that rely completely on templates are not well-suited to handle unstructured data. Intelligent process automation (IPA) tools, on the other hand, can handle this type of content and more. IPA uses Optical Character Recognition (OCR), Machine Learning (ML), and Natural Language Processing (NLP) to understand the context of a document, enabling it to identify and extract the information relevant to the process without having to create a template for every variation.

  2. Corporate Inbox Automation 

    In the Corporate Inbox use case, an intelligent automation tool processes incoming emails, deciphers the topic, and then routes them to an appropriate subject expert. For relatively simple matters, such as a change of address request, the IPA tool can extract the pertinent information and input it into an appropriate downstream system. An IPA tool can also extract and automate the handling of any attachments from emails, such as PDFs, spreadsheets, or Word documents. The IPA tool is smart enough to process the attachments and extract relevant information and then input it into another downstream system, such as a Customer Relationship Management system (CRM), for processing or storage for future reference.

  3. Customer Onboarding

    IPA can be used to classify and extract relevant unstructured data from customer-onboarding documents into an organization’s digital management system. This results in improved accuracy and efficiency for onboarding new customers, driving improved customer satisfaction, and increasing revenue for the company.

  4. Payroll Transactions

    Processing payroll repetitively every month is a time-consuming and mundane task for an organization’s HR team, since it requires a significant amount of effort dedicated to data entry. The manual data entry often results in inaccuracies that can lead to delays in payment and unhappy employees. IPA can reduce delays by checking the consistency of employee data across multiple systems and validating timesheets and deductions. IPA can also automate salary formulating processes, manage benefits and payments, and automate end-to-end payroll transactions to avoid inaccuracies and delays.

  5. Chatbots

    One of the largest users of chatbots is online shopping portals. Customers have different preferences, distinct orders, and product queries, etc., and implementing a chatbot serves to enhance their customers’ shopping experience and take care of mundane, repetitive tasks. While chatbots can provide relevant data, they may not be able to complete certain tasks unassisted. When integrated correctly, chatbots can feed data to an RPA bot to complete tasks like canceling an order or changing quantities or delivery dates based on certain criteria. This results in instant gratification to customers, enhancement of their shopping experience, and reduction of burden on the overloaded customer service executives.

Conclusion

As shown in the use cases above, RPA combined with AI technologies offers a broad spectrum of use-cases and can result in significant savings in terms of cost and time when leveraged properly. A successful RPA implementation depends on choosing the right tools and processes for automation. In addition, a heavy focus on the process itself will lead to the most meaningful results. As companies’ RPA strategies continue to develop, the utilization of RPA integrated with AI capabilities will continue to grow and quickly become the industry standard.

At Opteamix, we have deep expertise in both RPA and AI that helps organizations build their digital workforce. Our RPA solutions are tailored to your business’s needs and designed to deliver maximum efficiency with minimum disruption to the existing system. To learn more about what we do and how we can help you bring efficiency and reduce overhead costs, check out our RPA services page.

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Opteamix is a digital automation technology consulting firm with deep expertise in Application Development, Robotic Process Automation, AI, DevOps, Enterprise Mobility, and Test Automation Services. We are headquartered in Denver, Colorado with a wholly-owned delivery center in Bangalore, India.