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Software application development is benefiting from AI-assisted testing at the ‘back end’ of enterprise IT systems in order to make our business apps bug-free, more functionally complete and safer. Among the firms pushing forward AI tools of this kind is continuous testing and quality engineering company Tricentis. Now extending AI testing services with generative AI smartness, the company has now built a copilot service known as Tricentis Testim Copilot, which allows software testers to simply enter a text description of their test… and Testim Copilot generates the needed JavaScript code using generative AI, provides an explanation of selected code, or identifies and recommends fixes for potential issues.

With enterprises increasingly concerned about compliance, data use and Intellectual Property (IP) protection, Tricentis says that Testim Copilot has been designed to provide developer productivity gains and increased application quality without compromising on responsible usage, safety or accessibility.

This tool enables less technical testers to create custom tests without in-depth coding expertise. It explains test steps, making it easier to understand, document and reuse existing code. Further, it reduces the time and effort to debug test code by identifying issues and suggesting fixes. Additional Tricentis Copilot solutions for Tricentis Tosca and Tricentis qTest will be released later in 2024. 

Democratisation of testing 

“Based on initial customer experience with existing Tricentis AI-enabled products, we have seen an uplift of 20% to 50% in test case generation by the [application of] AI [in the way this product delivers it],” said Mav Turner, chief product and strategy officer, Tricentis. “In addition, customers utilising Tricentis AI tools have been able to lower their test failure rate by 16% to 43% so far. The democratisation of testing with AI will allow even less technical resources to participate in the creation and execution of AI-generated test cases, leading to faster completion, fewer errors, higher productivity, and reduced costs.”

The Tricentis AI-based, continuous testing portfolio of products provide a way to perform software testing with automated, fully codeless AI-driven functions that aligns with both Agile development and complex enterprise apps creation inside DevOps teams

“AI has been at the forefront of Tricentis’ product portfolio for several years and the launch of Tricentis Copilot marks the next step in that journey,” Turner continued. Testim Copilot puts AI into the hands of the user, automatically suggesting test cases and fixes, meaning more time spent on workflows to boost productivity and improve time to market for new applications. This is only the beginning – we expect future Tricentis Copilot releases to have even greater benefits.”

Pumping productivity

IDC estimates that enterprises will leverage generative AI and automation technologies to drive $1 trillion in productivity gains by 2026.

“Testing and automated software quality are a top area of expected benefit for generative AI over the next 12 months, according to IDC survey data and we have seen a majority of respondents expanding use, using or piloting the use of AI in conjunction with testing,” said Melinda Ballou, research director for IDC’s Agile ALM, quality & portfolio strategies. 

Ballou points to areas of focus here including test prioritisation, work designed to identify root cause of failure, automated test case creation and self-healing of test cases. She says that early investment in AI by test automation providers such as Tricentis when combined with actions to use pragmatically actionable data (as compared with the inefficiencies of manual testing) help drive better code quality and cost savings.

Are testers out of business? 

Will the emergence, enhancement and expansion of genAI-powered testing services put software application testing engineers out of business? Spoiler alert: no, of course not, please don’t be silly.


Because (as we all know) we need more enterprise software applications every day, we need more of those apps locked down for increasingly mission-critical use cases and we need more of the ancillary services that support application development itself, with testing fairly clearly ranking high up on the essential supporting services list. But why is all this happening most of all? Because AI is not going to replace developers, it is going to provide coders with additional support services that will make their time cutting code easier with less of the ‘rote’ drudgery factor.

Yes, some will argue that we will one day get to a point where all software programming and application development is rendered obsolete… but if you believe that, you Musk need some help.