If you’ve been following our blog for a while, we don’t need to convince you that Robotic Process Automation is rising. But in case you’re new here, here are a couple of RPA stats to help you understand its impact:
- By 2025, 4 million RPA bots will perform various office, administrative, and sales tasks.
- The RPA market value is expected to reach over $13 billion by 2030.
- Companies that adopted RPA report an average of 40% time savings in the first year.
But no matter if you’re an automation aficionado or an RPA rookie, one thing can’t be stressed enough: all that advancement wouldn’t be possible without RPA testing.
Proper testing reduces the overall cost and effort needed for a successful RPA implementation. Regardless, RPA testing is often neglected by RPA specialists and companies seeking to implement workflow automation. In this article, we’ll challenge that false notion by defining various types of RPA testing, explaining its role, and listing tools used in the process.
What is RPA testing, and why is it important?
Let’s be honest: complex RPA implementation requires an investment like any other software project. While small, single-process deployments are mostly affordable, license and implementation costs of large automation projects spanning multiple departments and applications may quickly add up. Still, companies agree to pay the price because the productivity boost far outweighs the initial expenditure. Provided RPA is working as intended.
If it’s not, the costs will continue to stack up. An RPA bot performs up to thousands of daily instances of the same task. Given this scope, even a single mistake can affect every single execution, generating severe losses before the error is detected. Then, the bot must be fixed, which takes even more precious time.
Luckily, there’s an easy way to increase the odds of a fast ROI and prevent costly errors and downtime. Yes, you guessed it: devoting some time before the launch to thoroughly test the bot.
What are the benefits of thorough RPA testing that make it a crucial stage of the implementation process? Let’s see.
Improved security
Testing RPA for cyber attacks, tampering, unauthorized access, and other dangers warrants that the automated process is secure and doesn’t put the organization and its members at risk. Identifying weak spots is one thing; another is checking the existing safety measures. Here, RPA testing helps verify if protection features, like logging, monitoring, user authentication, and access control, function correctly and can nullify the threats.
Preventing errors
One of the main advantages of RPA is reducing the margin of error for manual processes. However, this is only attainable if the bot doesn’t replicate or commit its own mistakes. RPA testing allows developers to identify errors early in the development cycle and ensure that the bots run the process consistently. This way, errors can be addressed before the launch, when fixing them becomes more challenging and expensive.
Quality assurance and improvements
Besides bug wrangling, RPA tests are essential to ensure that the RPA solution meets the desired performance standards. By running performance tests, RPA developers can spot inefficiencies before the launch so that the automated process is executed correctly. In some cases, testing the solution can even lead to new discoveries and guide developers toward tweaks that further enhance it.
Better user experience
Sometimes, particularly during more complex implementations, it’s easy to lose sight of how the final solution will be used daily. RPA tests are the perfect opportunity to see how end-users interact with it and ensure that the automated processes are user-friendly. It’s essential in the case of bots that will assist non-technical staff in everyday tasks like document retrieval or data entry.
Effectively, RPA testing leads to a better outcome for everyone:
- developers, who deliver a more reliable solution that they will require less of their time to maintain;
- end-users who enjoy a bug-free and more intuitive tool that expedites cumbersome work;
- business owners who see substantial growth in productivity and faster ROI on RPA implementations.

RPA testing methods
There are 5 main methods of RPA testing, each with its defined purpose.
- Unit testing — In unit testing, the performance of all RPA components and workflows is verified individually in both standard and edge cases. Breaking down the entire solution into smaller units and testing them individually allows automation developers to focus on one functionality or bot action, e.g., clicking a button or filling data fields. Thus, they can easily spot defects in specific areas.
- Integration testing — RPA workflows often rely on integrations between the automation platform and one or more business apps. The role of integration testing is to make sure that all third-party systems, APIs, and RPA components involved in the automated process are well-coordinated and can cooperate seamlessly, e.g., when moving data. Integration testing usually takes place once all relevant components have been unit-tested.
- Regression testing — RPA development is a gradual process. Constant modifications are necessary, but with each round of changes, there’s a chance that previously working code will crash, produce errors, or otherwise stop functioning. Regression tests focus strictly on these defects. Regression testing can involve other testing methods to pinpoint the change that causes the defect.
- Security testing — A separate risk assessment phase that verifies if necessary safety measures (governance, authentication, access control, traceability, etc.) are present and whether automation makes the organization vulnerable to any threats.
- User acceptance testing (UAT) — A user-oriented testing method that aims to confirm if the bot is executing the task as intended in terms of performance, usability, and functionality. In the case of attended RPA bots triggered by human employees, UAT also determines how intuitive and practical the automation is to its users.
It’s worth noting that since all testing methodologies have a distinct purpose, it’s not a matter of choosing one over another. Each of them has its use at different stages of development, and combining them is the best way to guarantee a secure, stable, and highly-performing RPA automation.