What Is Robotic Process Automation (RPA)?

For companies focused on cutting costs while boosting efficiency, robotic process automation (RPA) has become a go-to tool for automating repetitive tasks, streamlining workflows, and reducing human errors. But while RPA is valuable, it’s just one part of the solution when it comes to improving operational efficiency.

The real power of RPA comes when it’s combined with other intelligent technologies that improve the way companies discover processes, handle complex data, orchestrate their workflows, and get the most out of automation. Keep reading to learn how to maximize RPA with intelligent automation and the role RPA plays in the future of business.

Jump to:

What is RPA?
How does RPA work for enterprise companies?
What are the benefits of RPA for a business?
What are the different types of RPA?
What are the challenges of RPA?
RPA use cases and examples
What features and capabilities are important in robotic process automation technology?
How is RPA different from artificial intelligence?
The future of RPA and enterprise businesses

What is RPA?

RPA or robotic process automation is a technology that uses software robots to automate repetitive manual tasks traditionally done by humans, such as data entry, transaction processing, or report generation. These bots interact with digital systems to perform a range of tasks accurately, increasing efficiency and freeing up employees to focus on higher-value work.

How does RPA work for enterprise companies?

Robotic process automation (RPA) mechanizes simple manual work, taking on repetitive, rules-based processes—work that can often feel tedious or mundane to humans.

But, when combined with AI and smart technologies, RPA tools can tackle more complex processes and deliver more value to companies. For example, RPA can be integrated with process mining and intelligent document processing (IDP) solutions and technologies like natural language processing (NLP), pattern recognition, and automated learning to go beyond simple mechanization to handle less structured data. RPA can also be paired with AI, machine learning, and data analytics tools that perform human-like reasoning, decision-making, and interactions.

With proper planning and design, RPA can also connect to existing IT systems, including legacy platforms. This flexibility allows enterprises to implement RPA without major disruptions, gradually expanding automation across departments for a tailored approach to digital transformation.

What are the benefits of RPA for a business?

The most widely recognized advantage of robotic process automation (RPA), especially when combined with other intelligent technology, is its ability to dramatically boost productivity. After all, RPA bots can run 24/7 without getting tired or making mistakes. However, RPA also offers many other important benefits:

Cost reduction

RPA is a potent tool for reducing costs, not just by speeding up workflows and executing more transactions in less time, but by improving accuracy and reducing costly human errors in mundane, repetitive digital tasks. Plus, with smart planning, RPA solutions can work seamlessly with existing IT systems, letting businesses delay expensive platform upgrades.

Employee experience

By liberating employees from repetitive tasks, RPA allows people to engage in more high value, intellectually stimulating activities that align with their expertise. This shift increases job satisfaction, leading to better retention and a more motivated workforce. In fact, in a global survey, 20% of IT decision makers pointed to employee pressure—and 35% to reducing employee burnout—as their reason for implementing automation technologies.

Improved compliance

RPA can also be a powerful tool for improving compliance by automating repetitive processes and executing them at scale consistently and accurately, without human error. For more complex tasks, IDP can extract and interpret complex, unstructured information and put it in a structured, digital format that RPA systems can process. By combining RPA with IDP, companies can not only automate compliance tasks but also handle a wider variety of data, making the entire compliance process more efficient and reliable.

Digital transformation

RPA alone automates simple tasks, but when combined with technologies like process intelligence and low-code development tools, can deliver intelligent process automation (IPA)—key for innovative digital transformation. IPA can help businesses extend RPA to more complex tasks as well as ensure businesses are applying automation where it has the greatest impact.

What are the different types of RPA?

The amount of human involvement needed in a process helps determine the right RPA solution for you. Let’s explore the different types of RPA and look into why certain processes are better suited for each one.

Attended RPA

Attended RPA works alongside employees and is activated as needed to help handle processes that still require some human intervention or decision-making. In customer service environments, for example, attended RPA bots might take care of routine tasks like data entry to pre-fill forms, while employees review or verify the information.

Unattended RPA

In contrast to attended RPA, unattended RPA operates completely independently. Ideal for back-office tasks like data migration or report generation, these tools run in the background on servers or desktops, performing tasks from start to finish according to preset rules and schedules—no human supervision required.

Hybrid RPA

Hybrid RPA blends the best of attended and unattended RPA through human-machine collaboration. With hybrid RPA, some parts of a workflow are managed by humans working alongside attended bots, while other parts are fully automated with unattended bots. This setup is ideal for complex processes such as insurance claims, where unattended bots can process the claims and extract data, while employees step in to handle exceptions.

What are the challenges of RPA?

The challenges businesses encounter with RPA are often a result of the rule-based nature of RPA and implementing RPA without cognitive skills. Here are some common obstacles companies face when integrating RPA, along with solutions that can help overcome them.

Selecting the right processes for automation

Too often, companies jump into automation without a clear sense of how their current processes work. Investing time and money to automate a task, only to realize this step could have been eliminated altogether, is a costly mistake. That’s why, before diving into RPA, enterprises must carefully analyze their processes to pinpoint the best opportunities for automation. Process mining is a valuable solution for this, helping to identify bottlenecks and efficiencies to optimize automation strategies from the start. By conducting thorough analysis upfront—identifying bottlenecks and predicting outcomes—businesses can ensure RPA is deployed where it will make the biggest impact.

Tackling unstructured data

Simple RPA bots manage repetitive, rule-based tasks well, but struggle with unstructured content like emails, invoices, healthcare forms, and logistics documents. As a result, getting information out of non-standard documents and forms often requires human intervention. However, when used alongside technologies like natural language processing (NLP), optical character recognition (OCR), and other advanced capabilities found in intelligent document processing (IDP)—RPA capabilities can be extended to even manage unstructured data and more complex workflows.

Making judgement-based decisions

By itself, RPA can’t "think" or understand the reasoning behind certain actions, meaning it cannot deal with exceptions or make detailed decisions requiring judgment. Without the ability to learn or adapt, RPA also struggles with workflows that demand flexibility in response to evolving business needs. To address this, enterprises can pair RPA with cognitive automation or AI technologies that can interpret data, learn from patterns, and make context-based decisions, streamlining judgment-driven operations.

Monitoring after implementation

Deploying RPA is just the beginning. Beyond exception handling and dealing with system changes, to ensure the system delivers continuous improvements, you need ongoing monitoring and analysis. Process intelligence tools can help with this, tracking and optimizing performance over the long term.

Employee resistance to automation

Process changes aren’t always popular, even when they ultimately improve workflows. For employees, automation can bring up everything from concerns about job security to frustration about having to learn and adapt to new ways of doing things. To allow for smoother transitions, businesses can engage employees early in the process so they feel empowered, not threatened, by automation.

RPA use cases and examples

Robotic process automation (RPA) is valuable across industries because its core functions—improving efficiency, reducing costs, and mechanizing routine work—are universal needs. However, certain industries have specific use cases that make RPA even more impactful.

Financial services

For banks and financial institutions, RPA can help automate Know Your Customer (KYC) and anti-money laundering (AML) compliance activities. These operations involve gathering and verifying a lot of customer information from multiple systems to meet regulatory standards.

To handle these processes, RPA needs to be combined with intelligent document processing (IDP), which can interpret and process complex, unstructured data, enabling more comprehensive automation. With the support of IDP, RPA can quickly pull data from various sources, check it against compliance databases, and flag suspicious activities for further review. In trade finance, this combination can also be used to streamline document handling and transaction verification for international trade.

Insurance

In insurance, RPA is often used in conjunction with IDP in claims adjudication. IDP pulls unstructured data from documents such as policy details, medical records, or damage reports, and helps RPA auto-verify the accuracy and validity of claims by cross-referencing claim data. This reduces delays in claims approval and processing. RPA with IDP is also used in underwriting to pull and analyze customer data from multiple sources for more precise risk assessments.

Healthcare

Hospitals and healthcare organizations rely on RPA to streamline patient scheduling and support revenue cycle management. However, to truly optimize these processes, RPA can be combined with a process intelligence tool, which analyzes workflows and identifies where automation can make the biggest impact.

By integrating process intelligence, healthcare organizations can make even smarter use of RPA, ensuring that automation is applied strategically for the best results. Additionally, RPA—with the help of IDP—can make sure that electronic health records (EHRs) are consistently updated across multiple systems. This not only makes patient data more accessible but also eases the administrative workload for healthcare staff.

Transportation and logistics

In transportation and logistics, RPA helps automate customs and border processing by handling customs declaration submissions. While RPA can manage this if the data is structured and digital, more complex tasks involving unstructured documents like invoices or bills of lading require intelligent document processing (IDP) to extract and process the necessary information.

Used together, RPA and IDP can reduce delays and compliance issues by ensuring all necessary documentation is in place for cross-border shipments. In fleet management, RPA can automatically monitor structured data such as vehicle performance, maintenance schedules, and compliance with safety regulations to optimize operations and reduce downtime. Handling more complex tasks like analyzing unstructured reports or identifying patterns across large datasets requires using RPA in conjunction with process intelligence and IDP technologies.

What features and capabilities are important in robotic process automation technology?

Key features of RPA solutions include the ability to follow predefined business rules and automate repetitive tasks. To address operational concerns, RPA technology also needs robust security measures and strong error-handling and recovery capabilities.

Your RPA solution must also connect with existing business systems, including legacy platforms, via user interfaces, APIs, and other methods. This allows RPA bots to operate across different environments, scaling automation on an enterprise-wide level.

To handle more complex processes, integrating RPA with intelligent solutions like IDP and low-code tools becomes crucial. To truly realize the full potential of RPA, implement it with a holistic approach, considering the entire workflow from start to finish. Combining RPA with intelligent technologies enhances its effectiveness by helping companies identify the most impactful areas for automation and apply cognitive capabilities to automate even complex workflows. Now, let’s explore some of the key tools that can help you unlock this potential.

RPA and intelligent automation

RPA excels at mimicking human actions by following predefined rules, but falls short when it comes to making decisions requiring judgement. That’s where intelligent automation (IA) can help. By combining RPA with technologies like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), IA reshapes automation into something far more dynamic, managing operations that require interpretation and learning.

RPA in conjunction with IA can tackle unstructured data and make context-based choices. Together, RPA and IA create a dynamic system that can automate more complex processes.

RPA and process mining

Process mining is a technique that analyzes data from business systems to visualize and understand how processes are actually working. It dives deep into your systems, uncovering bottlenecks and deviations, to give you the insights needed to optimize and improve. By pinpointing which workflows are best suited for automation, process mining helps ensure your RPA investment is applied where it will make the biggest impact.

Even after RPA is up and running, process mining continues to play a key role by monitoring automated processes in real time, providing alerts for compliance and optimization. This ongoing visibility allows businesses to refine and enhance their efforts, so processes continue to run effectively.

The future of RPA and enterprise businesses

RPA's evolution hinges on its continued integration with AI and other technologies. Businesses today need RPA solutions that enable intelligent automation: delivering smart, holistic solutions capable of running decision-driven workflows with intelligence and flexibility across entire organizations.

ABBYY helps businesses achieve these transformative solutions by providing essential technologies like intelligent document processing (IDP) and process intelligence, enabling businesses to get the most out of their existing RPA systems. We make RPA bots more capable by giving them the ability to intelligently read and understand document data, both structured and unstructured, to make smart decisions.

We work with top RPA vendors including Blue Prism, UiPath, and Automation Anywhere, offering easy integration with our no-code, cloud-first platform. Plus, our process mining platform ABBYY Timeline allows businesses to analyze their workflows as they happen to make smarter decisions about where to implement RPA for maximum impact—and to monitor the performance of automated workflows to ensure continuous improvement.

Reach out to us for an introductory demo and learn how ABBYY’s intelligent automation solutions can transform and streamline your workflows.