It is a well-known challenge that business users and subject matter experts are brought into projects and given responsibility for testing — often without formal knowledge of test design or testing practices. We frequently observe resistance, particularly toward documentation and structured test case design. Many business specialists perceive testing as time-consuming bureaucracy and struggle to see the value of documenting test cases. Combined with limited testing competencies, this can create skepticism and even friction toward the testing discipline itself.
With the introduction of GenAI tools such as ChatGPT, we see a potential turning point. In several client cases, we have introduced GenAI to support business testers in generating structured test cases and documentation for SIT and/or UAT. Interestingly, the reaction was not fear — but curiosity. The perceived burden decreased, documentation process improved, and business stakeholders became more open to structured testing practices, and collaboration with the QA specialists in general.
As of now, our observations are based on three client cases across different organizations and project contexts. We expect to expand the study with additional cases before the conference. Our approach combines qualitative interviews with business stakeholders, along with quantitative questionnaires focusing on perceived effort, confidence in quality, and attitude toward testing before and after the introduction of GenAI.
This raises a deeper question: How does the introduction of GenAI influence the mindset of business testers — and how does it impact their confidence in quality?
Our vision is not that AI replaces human judgment, but that it may reshape the relationship between business stakeholders and the QA discipline, including the relationship with professional testers. We explore whether GenAI can act as a bridge between human expertise and the prioritization of structured quality practices. Participants will leave with a new perspective on how hybrid human–AI collaboration can influence not just efficiency - but mindset, ownership, and confidence in quality.
- Does AI reduce resistance toward test documentation?
- Does it increase trust in quality — or create overconfidence?
- Does pre-generated test content reduce exploratory thinking?
- Does the way we introduce AI influence its impact?
- What cognitive biases might be amplified when AI generates test cases?
- QA leaders and Test Managers working with business-driven testing
- Organizations introducing GenAI into QA workflows
- Product Owners and Business Specialists involved in (acceptance) testing
- Agile leaders and transformation roles exploring hybrid human–AI collaboration
- Anyone interested in the psychology of testing and AI adoption