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Can AI Solve Test Automation Engineer Shortages?

The test automation industry is rapidly transitioning towards artificial intelligence to tackle challenging issues. AI can decipher subtle changes in a GUI, learn patterns for recommendations, consume massive data, take on repetitive tasks, and can potentially reduce development costs. But can it address the shortage of skilled test automation engineers?

“Artificial Intelligence is transforming software testing by not only automating manual tasks but learning of changes and automatically adapting. This helps save time which reduces costs. It can also point out signals for managers to make better data-driven decisions.” Source: How AI is transforming software testing

There are a lot of tools and programming languages test automation engineers need to possess. There are plenty of jobs of this ilk, however, most go unfilled or take a long time to fulfill. Most companies are seeking specialists rather than generalists. According to a hiring manager, the majority of those prospects he’s interviewed either lack the required technical skills or have no comprehension of QA and testing principles.

Statistics: Struggle to Find Best Test Automation Tool. Source: Autify

In a study, one of the greatest struggles companies face with test automation is finding the right tools, followed by training/acquiring skilled automation engineers. Tools and people are common obstacles here. Regarding the latter, artificial intelligence is one of the key indicators for overcoming the challenges of humans. We don’t anticipate it to eliminate jobs, but used as a tool to produce superior software, faster.


It is evident there is a test automation engineer shortage. However, the industry is making significant strides in test automation. Based on stats, between 10 percent and 49 percent of a company’s overall QA budget is invested in test automation related expenditures. And larger companies — those with 500 or more employees — are more than twice as likely to spend over 75 percent of their QA budget on test automation.

So, can artificial intelligence solve test automation engineer shortages? I believe it can, as the investment prioritization is there for many companies. DevOps teams are always exploring better tools. Since new tools are introducing AI learning algorithms into their platforms, this will rid the need for such a scarce role, and place the responsibility back on testers. Some codeless AI-based testing platforms are so user-friendly, they require no coding of test scripts, nor maintaining them. This means less skilled individuals on the QA team can learn and apply the testing software to the lifecycle.

Are you a test automation engineer? Are you a tester? Or apart of a software quality assurance team? I’d like to hear your thoughts on this perplexing question in the comments!


Kobiton-Infostretch State of Test Automation (2020-2021)
Autify’s Mind-Blowing DevOps Testing Stats (2020)

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