What’s AI-Powered Robotic Automation (RPA)?

Robotic Process Automation (RPA) is a process of assigning robots to perform repetitive, rule-based duties. Such duties include manipulating data, processing paperwork, and even responding to customer queries. Robots are able to perform these tasks efficiently and free of errors or downtime, giving human staff the confidence to focus on high-priority tasks.

How Does Robotic Process Automation (RPA) Work?

RPA typically works in the form of a program or software that accesses information with legacy solutions. With automation scripts, RPA carries out specific tasks in mostly front-end integrations. With these features, RPAs can log into accounts, change settings, and take data from one system and apply it to another.

Benefits of RPA

Companies that implement RPA into their systems will experience positive changes in many different ways. These changes are as follows:

• Less manual labor: RPA takes the hard work and repetition out of various tasks — even reducing or eliminating the need for programming skills.
• Minimal errors: The rule-based nature of RPA almost guarantees a mistake-free environment due to less human involvement.
• Workflow optimization: RPA improves efficiency without disrupting pre-existing systems in place, reducing bottlenecking and the need for manual supervision.
• Greater return on investment (ROI): As RPA works to make teams more productive overall, more work as a whole gets accomplished in a given time, thus opening up more opportunities for revenue.
• Consistent performance: In terms of customer support, RPA can work to help customers get what they need regardless of time of day or other factors, in turn reducing human support tickets and maintaining a high employee morale.

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Types of RPA: Attended vs. Unattended

There are two primary types of RPA to consider. Attended RPA deploys robots that work alongside human staff to make work easier and go faster. Unattended RPA deploys robots that don’t rely on human intervention, so they accomplish tasks by themselves.

Here are the advantages and disadvantages of both types of RPA:

Robotic Process Automation Use Cases Across Industries

RPA is used in many different industries to bolster business overall from enterprise companies like the Home Depot to local banks or credit unions. Here are some specific scenarios where RPA gets implements in certain verticals:

Robotic Process Automation in Healthcare

When it comes to medical billing, accuracy is paramount in order for bills and insurance claims to be properly filed and processed the first time around. RPA software is certainly helpful for medical facilities and hospitals when completing forms, keeping track of medical records, and creating prescriptions for patients.

Robotic Process Automation in Insurance

The insurance industry involves a lot of repetition to improve customer experiences. Like in healthcare, automated solutions can help file claims seamlessly, but it can also work to simplify the underwriting process, and provide adequate customer support.

Robotic Process Automation in Accounting

Accounting is another vertical where RPA can be a tremendous help. Over 33% of bots today are used to serve the finance industry in some form. The tasks in which RPAs can get involved with operations include data entry, account reconciliation, financial report writing, invoicing, and auditing. 

AI-Powered Robotic Process Automation vs. Traditional Automation

Machines are capable of doing almost any sort of task today, but there are two different approaches to automation: RPA and traditional automation.

While RPA solutions can handle front-end tasks on an interface level, traditional automation is developed to handle back-end and technical tasks within a program or platform. Traditional automation can be made to handle complex tasks, while RPA is usually made to be versatile and convenient for different businesses. Little to no coding is required for implementing RPA, whereas traditional automation requires programming prowess and well as a significant amount of time to refine it.

Both approaches are useful in their own ways, and one approach can’t outright replace the other any time soon.

Scaling RPA in Enterprises

Due to the rule-based nature of RPAs, many businesses have found it a challenge to scale their RPA solutions to suit their changing needs. Being able to successfully scale RPA comes down to choosing the best demand generation methodology:

1. Comprehensive Analysis: Acknowledges small, simple requests within the company.
2. Design Thinking Workshop: Acknowledges complex requests across multiple businesses (ie: customer service).‍
3. Process Mining: Provides foresight to identify a company’s automation needs.