Three Ways AI Is Revolutionizing Software Test Automation

October 07, 2021


Three Ways AI Is Revolutionizing Software Test Automation

Test automation has improved the software development process significantly by adding speed and accuracy, making it possible for software developers to match supply with demand. But then, the advent of artificial intelligence is set to make software development even better. This article will investigate some of the changes that will come with using AI for software test automation.

Making Testing Faster, Better, and Cheaper

You cannot talk about the benefits of technology without mentioning speed. Wherever technology has been applied, it has made things run faster. The software testing process is no exception. Automation has increased testing speeds, making it possible to complete many tests within a short time.

Artificial intelligence has further increased test automation speeds. It helps testers create scripts quickly, which makes it possible to complete more tests within a short time.

Besides speed, there’s a higher level of accuracy when using AI software testing tools. These tools bring the best out of software testing teams. All you need to do as an organization is train your testing team on how to use AI tools. Various online resources are there to help them learn automation testing.

Experts have designed these resources for beginner testers with the goal of helping them develop testing skills, especially when using software testing tools. In the end, this will save a lot of money as these tools will help mitigate human errors in the software testing process.

Reduce Work for the Tester

Before automation, software testers had a significant amount of work to do. But this workload has been reducing over time as technology is applied in the software testing industry. Automation came as a lifesaver in most organizations since it relieved software testers of around 20% - 30% of their work.

For instance, software testing tools have helped ensure that organizations execute test cases constantly. This wasn’t possible with humans because there could be delays along the way. Besides, software testing is repetitive, and this monotony could overwhelm humans leading to mistakes along the way.

AI has made work even easier for software testers. Decision-making, a vital step to proper software testing, has become faster and more effective. AI does most of the work for software testers, including gathering important data and analyzing it. Thus, all testers need to do is make decisions from this data.

Testers can invest their extra time in other tasks that are more demanding or that could bring more revenue. increases productivity, impacts software quality, and reduces the time spent to market the products.

Help Identify What and Where to Test

A software tester’s job includes identifying what they need to test. This is one of the tasks that software testers no longer need to worry about, thanks to technology. AI software testing tools help testers identify the subsets of test cases they need to perform instead of having a human do it.

AI has simplified this, making it easier to do and more effective in the end. Today, you don’t have to worry about most tasks that lead to test development if you are leveraging software testing tools. All you need to do is the software tool initial setup, and it will do the rest for you.

These tools can help software testers identify the bugs that exist in software. Highlighting them helps testers know where they can put effort and testing resources more profitably. Besides, AI testing tools make it possible to find duplicate failures in the software after testing.


There’s no doubt that the AI revolution will come with many positives for the software industry. It will be up to testers to leverage the power of this technology.

Using AI will make it easier to perform automated UI testing that ensures better software usability. AI is also going to improve end-to-end testing and overall software security, and will also increase efficiency in the software development process. This will make the 20-30% fully automated testing more effective.

Dan has hands-on experience in digital marketing since 2007. He has been building teams and coaching others to foster innovation and solve real-time problems. Dan also enjoys photography and traveling.

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