Applause, the global leader in managed software testing services and digital quality, released The State of Digital Quality in Functional Testing 2026, its fifth annual industry report on global QA trends, revealing a dramatic acceleration in AI adoption in development and testing. Findings indicate more than 92% of respondents use AI in the testing process, up from 60% last year, while only 8% say they don’t use AI for any aspect of testing. However, increased AI adoption has not led to fewer issues: 29% reported an increase in the number or severity of functional testing defects, and another 15% said both the number and severity of functional testing issues have increased.
The findings highlight AI’s massive impact on the software development and QA community. For nearly nine in 10 respondents (89%), AI has changed the way they test applications and digital experiences, while 86% consider human involvement extremely important to functional testing. More than half (57%) emphasised that humans are critical for delivering qualitative feedback through peer review. The same number of respondents believe humans are equally important to designing test strategies based on real-world user behaviour.
As organizations increasingly use AI in both development and testing, the results underscore the need to determine the right balance of AI, automation and human expertise to maintain quality while keeping pace with faster release cycles.
“AI has accelerated the development process, and that’s changing what teams need to test and how they need to test it,” said Tacita Morway, Chief Technology Officer, Applause. “Traditional automated testing answers the question: can this task be completed? A human tester answers a harder one: could a real person work out how to do this, and get it done? Teams are giving up that second question as release cycles get faster than people can keep up with, and I think that accounts for a lot of the defect increase we’re seeing. The work now is to get that kind of human testing coverage back, but at machine speed. That takes AI, automation and people together.”
Morway continued, “This gets harder with evaluating agentic systems that make decisions and take action on their own. With an agent, there’s no fixed set of steps to check — the same request can take a different path every time. The failures that matter most happen when the system is effectively making a judgment call and gets it wrong — inaccurate financial transactions, exposed sensitive information, dangerous guidance. Those carry real consequences for organizations and their customers, and you can’t catch them by confirming a script still passes. Systems this powerful and this unpredictable need a materially different approach to evaluation.”
In addition, the survey found that AI has had a greater impact on development than testing, although that gap is closing. Respondents are broadly aligned on whether AI has had a slight, moderate or significant impact on development and QA. Overall, 79% believe that AI has had a significant or moderate impact on development compared with 72% for testing. Less than 10% said AI has had no impact at all on development (3%) or quality assurance (9%).
Regardless, AI use cases in development and testing are growing in number and popularity. 62% of respondents now use AI to generate or complete code with in-editor coding assistants, while 59% use it to review code and create documentation. On the testing side, the most common use cases are creating test cases (65%), writing test automation scripts (62%), and finding and addressing coverage gaps (48%). As a result, 66% of organizations have documented policies around AI use in development and testing, with 20% considering their guidelines “clear and robust.”
“Shipping faster only helps if you can still trust what you’re shipping. That means testing that’s grounded in real-world context and backed by human expertise,” continued Morway. “Our survey showed 86% of respondents understand that human involvement is essential to functional testing — but many of those organizations are struggling to preserve that human perspective while supporting faster development. Traditional automation doesn’t solve that. Intelligent automation does — grounded in the product, the user and the risks that matter. Human expertise helps shape what gets tested and how, and fills the gaps where automation can’t or shouldn’t.”
Applause’s State of Digital Quality content series provides insight into the latest software testing and QA practices and trends, including preferred methods and tools, as well as common challenges faced by software development and testing professionals worldwide. The most recent report is based on Applause’s August 2026 global survey of industry experts and professionals, plus interviews with technology leaders about AI’s growing role in software development and testing and its impact on digital quality.
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