AI is rapidly becoming part of the software delivery toolkit — but for many testing and QA teams, the question isn’t whether to use AI, it’s how to use it well.

In this session, we’ll explore how AI can act as a testing partner, augmenting human judgment rather than replacing it. You’ll learn practical strategies for integrating AI into testing workflows in ways that improve speed, insight, and quality — without introducing unnecessary risk or erosion of testing discipline.

This webinar is designed for software testers, QA professionals, and engineering teams who want to move beyond experimentation and understand what responsible, effective AI usage actually looks like in day-to-day testing work.

What You’ll Learn

• Where AI adds real value in software testing — and where it doesn’t
• How to collaborate with AI while maintaining test rigor and accountability
• Common mistakes teams make when adopting AI for testing
• Patterns for using AI to enhance insight, coverage, and decision-making
• How testing teams can lead (not lag) as AI becomes embedded in the SDLC

Who Should Attend

• Software testers and QA professionals
• Test leads and managers
• Software engineers involved in quality and delivery
• Engineering leaders exploring responsible AI adoption

Why This Matters Now

As organizations look to scale AI across software engineering, testing teams play a critical role in ensuring outputs are reliable, explainable, and fit for purpose. Understanding how to partner effectively with AI is quickly becoming a core capability — not a nice-to-have.