Robotic process automation, also known as software robotics, uses intelligent automation technologies to perform repetitive office tasks of human workers, such as extracting data, filling in forms, moving files, and more.
RPA combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts, which copy human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.
This form of automation uses rule-based software to perform business process activities at a high volume, releasing up human resources to prioritize more complex tasks. Robotic process automation enables CIOs and other decision-makers to accelerate their digital transformation efforts and generate a higher return on investment (ROI) from their staff.
RPA and Intelligent Automation
In order for RPA tools in the marketplace to remain competitive, they need to move beyond task automation and expand their offerings to include intelligent automation (IA). This type of automation expands on RPA functionality by incorporating subdisciplines of artificial intelligence, like machine learning, natural language processing, and computer vision.
Intelligent process automation demands more than the simple rule-based systems of RPA. You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and “learning,” respectively. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way.
Industry Newsletter
The latest tech news, backed by expert insights. Stay up to date on the most important and intriguing industry trends on AI, automation, data, and beyond with the Autoloopers newsletter. See the Autoloopers Privacy Statement.
RPA and Artificial Intelligence
Robotic process automation is often mistaken for artificial intelligence (AI), but the two are distinctly different. AI combines cognitive automation, machine learning (ML), natural language processing (NLP), reasoning, hypothesis generation, and analysis.
The critical difference is that RPA is process-driven, whereas AI is data-driven. RPA bots can follow only the processes defined by an end user, while AI bots use machine learning to recognize patterns in data, in particular unstructured data, and learn over time. Put differently, AI is intended to simulate human intelligence, while RPA is solely for replicating human-directed tasks. While the use of artificial intelligence and RPA tools minimizes the need for human intervention, how they automate processes is different.
That said, RPA and AI also complement each other well. AI can help RPA automate tasks more fully and handle more complex use cases. RPA also enables AI insights to be acted on more quickly instead of waiting on manual implementations.
How Does RPA Work?
According to industry standards, RPA software tools must include the following core capabilities:
- Low-code capabilities to build automation scripts.
- Integration with enterprise applications.
- Orchestration and administration including configuration, monitoring, and security.
Automation technology, like robotic process automation, can also access information through legacy systems, integrating well with other applications through front-end integrations. This allows the automation platform to behave similarly to a human worker, performing routine tasks, such as logging in and copying and pasting from one system to another. While back-end connections to databases and enterprise web services also assist in automation, RPA’s real value is in its quick and simple front-end integrations.
The Benefits of RPA
There are multiple benefits of implementing robotic process automation, including:
- Less coding: RPA does not necessarily require a developer to configure; drag-and-drop features in user interfaces make it easier to onboard nontechnical staff.
- Rapid cost savings: Because RPA reduces the workload of teams, staff can be reallocated to other priority work that does require human input, leading to increases in productivity and ROI.
- Higher customer satisfaction: Because bots and chatbots can work around the clock, they can reduce the wait times for customers, leading to higher rates of customer satisfaction.
- Improved employee morale: By lifting the repetitive, high-volume workload off your team, RPA allows people to focus on more thoughtful and strategic decision-making.
- Better accuracy and compliance: As you can program RPA robots to follow specific workflows and rules, you can reduce human error, particularly around work that requires accuracy and compliance, like regulatory standards.
Challenges of RPA
While RPA software can help an enterprise grow, there are some obstacles, such as organizational culture, technical issues, and scaling.
Organizational Culture: While RPA will reduce the need for certain job roles, it will also drive growth in new roles to tackle more complex tasks. Organizations will need to promote a culture of learning and innovation as responsibilities within job roles shift.
Difficulty in Scaling: While RPA can perform multiple simultaneous operations, it can prove difficult to scale in an enterprise due to regulatory updates or internal changes. A company must have 100 or more active working robots to qualify as an advanced program, but few RPA initiatives progress beyond the first 10 bots without expert guidance.
RPA Use Cases
There are several industries that leverage robotic process automation technology to streamline their business operations:
- Banking and Financial Services: Many major banks use RPA solutions to automate tasks such as customer research, account opening, inquiry processing, and anti-money laundering.
- Insurance: Insurance is full of repetitive processes well suited for automation, including claims processing operations, regulatory compliance, and policy management.
- Retail: The rise of e-commerce has made RPA an integral component of the modern retail industry, improving back-office operations and customer relationship management.
- Healthcare: Accuracy and compliance are paramount in healthcare. Large hospitals use RPA to optimize information management, prescription management, and payment cycles.
Explore our trial at Autoloopers to start your automation journey today.
