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Tricentis has published its second annual Quality Transformation Report, based on a survey examining increasing complexity in today’s software development lifecycle. The findings indicate that while AI is enabling faster software development, it is also associated with additional risks to software quality.
With an emphasis on rapid business transformation, AI technologies are being used to increase development speed. At the same time, the report notes that deployment practices in some organisations include releasing untested code into production. This trend is linked in the survey responses to executive pressure as well as the growing volume of AI-generated code, highlighting a gap between speed and quality priorities.
In 2026, despite advancements in AI tools, 60% of organisations report that they still deploy untested code. The majority of these organisations cite leadership pressure as a key contributing factor.
The financial services and retail sectors report higher levels of operational strain, with over half of organisations in these industries indicating impacts related to these practices.
Although 48% of surveyed companies have fully integrated AI into their workflows, more than half report frequent changes in AI tools, which adds complexity to quality management processes.
The report also identifies differences in perception within organisations, with higher levels of executive confidence in AI compared to more cautious views among staff.
Financial impacts related to software quality are also reported. A significant number of organisations indicate financial losses linked to software quality issues, along with increased rework and technical debt associated with reduced emphasis on quality assurance.
Around 20% of companies report annual losses exceeding $1 million due to quality-related issues.
The primary concerns highlighted in the report relate to security compliance and software quality risks.
Overall, the report describes a landscape in which AI adoption is increasing development speed while also introducing new challenges for maintaining software quality, with organisations working to align engineering practices and business objectives.
