Modern-day automation tools have adopted 4.0 technologies over the years of their evolution. Part of this adoption uses robotic process automation (RPA), artificial intelligence, and machine learning to make the execution of tasks in different IT branches, businesses, and industries faster. Software testing has also been experiencing use for certain tools that are enhanced by automation so that the work of developers is seamless.

The terms “RPA tools” and “test automation tools” tend to be used interchangeably, but they are not the same. Understanding these differences will allow any stakeholders that are involved in a company to make a more informed decision when it comes to RPA and software testing.

RPA has been covered in-depth in many Digital Workforce Solutions blogs, so this section will act as a refresher for those that have had some time away from RPA. Robotic process automation refers to technologies that can interact with tools, IT infrastructure, and business processes with the aid of AI and ML to learn a task and automate it. RPA is very useful for data-intensive tasks because it can take over repetitive tasks involved in workflow processes so that human workers can focus on more important tasks. Accuracy, efficiency, and productivity are all improved, and scalability is possible because of end-to-end structuring which allows the bots involved to learn and interpret data for specific processes.

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Test automation is a method in software testing that uses tools to learn about information, extract that information, and control how software tests are executed. Instead of focusing on workflow and processes, test automation automates repetitive cases that are found during tests. Test cases can become very repetitive and redundant, especially when a massive IT project is being worked on. With so much repetition, testing processes can become more prone to errors and increase the time it takes to complete projects. Delivery can also be negatively impacted because bugs can be overlooked. Most of the current testing tools use AI and provide cross platforms that allow the integration of other tools.

Overall, RPA and test automation are similar due to the fact that both are used to reduce manual repetitive processes so that productivity and quality of output are increased.

The difference in goals: Both processes automate different goals. Test automation focuses on software test automation and RPA focuses on mundane, repetitive business processes that can include software test automation.

The difference in coding: You need a certain level of coding knowledge for test automation because different software has different code structures. IT personnel can choose between JAVA, VBA, Python, and other low-code or no-code platforms.

With RPA, you don’t need any knowledge about programming. RPA platforms use drag-and-drop features so that you can automate tasks. If you want to get into the advanced side of RPA, someone will need to understand a programming language to access and manipulate base codes.

The difference in application scaling: Test automation is implemented for a small section of a company for software applications that already exist. Some sections of a company could be research and development, quality control, and IT engineering teams. RPA is used for a full department and looks to link processes between more than one department. RPA also allows company data to be centralized so that it’s easier to access and analyze.

RPA and test automation are platform-independent and both of them are trying to improve the quality of goods or services that a company offers. Depending on what you need to achieve, teams can decide which kind of automation is best for their next automation project.