"Based on responses from more than 300 engineers and IT decision-makers, the research indicates that enthusiasm for AI-enabled testing is high. Nearly nine in ten respondents said AI now ranks as a priority within their testing strategy, and four out of five expect it to improve testing outcomes over the next two years. Yet that optimism has not translated into broad, end-to-end deployment."
"The trust factor is slowing adoption of AI. More than half of respondents said concerns about quality and dependability are limiting wider AI adoption. Testing teams reported that unstable or brittle tests, along with the difficulty of automating complex processes that span multiple systems, continue to create friction. Updating test suites after changes to critical applications also remains time-consuming. 45% said it takes three days or longer to revise tests following significant system updates, delaying release cycles and dampening confidence in automation tools."
A global survey of more than 300 engineers and IT decision-makers finds strong enthusiasm for AI-enabled testing: nearly nine in ten respondents rank AI as a priority and four out of five expect it to improve testing outcomes within two years. Adoption remains limited: 65% are experimenting with or using AI in some testing activities, while only 12.6% have embedded AI across core test workflows. Quality and dependability concerns are primary barriers, with unstable or brittle tests and the difficulty of automating complex, multi-system processes creating friction. Test updates are time-consuming and only 41% of testing is automated.
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