Mastering Quality Engineering in AI Era

As Artificial Intelligence(AI) and Machine Learning(ML) continues to reshape the software landscape, the role of Quality Engineering (QE) is undergoing a significant transformation evolving into a more strategic, data-centric, and innovation-driven discipline. Quality engineers are now positioned to harness AI as a powerful tool to enhance efficiency, increase test coverage, and accelerate decision-making across the software development lifecycle.

This paper explores the growing impact of AI on QE, the challenges organizations face in adopting AI-driven testing practices, and strategies for leveraging AI to optimize quality assurance. It aims to provide QE professionals with the insights and guidance needed to stay ahead in an increasingly AI-enabled world.

Paper | Presentation

 Nishadhi Nikalandawatte

Accomplished Software QE Strategist and a Thought Leader with over 21+ years of industry experience. Excels in developing comprehensive testing strategies, automation frameworks, and end-to-end test solutions across various sectors, including technology, travel, hospitality, healthcare and non-profit. Passionate about advocating for quality within organizations and thrives on working with others, coaching, mentoring, and building high-performing teams. Currently leading the quality engineering practice at Slalom Seattle, establishing best practices, strategies, and go-to-market solutions for the practice.