Power to the Testers – How AI & ML Enables QA to Build Efficient DevOps Cycles and Propel Organizations into the Next Normal
AI isn’t the future of testing; it’s the present-day reality, with ever-increasing significance as organizations are propelling into the next normal. Intelligent technologies such as artificial intelligence (AI), machine learning (ML) and analytics are becoming important building blocks of intelligent platform solutions for software companies and IT organizations in 2021. The aim of such intelligent platforms is to provide people with sustainable support so that processes can be optimized and maintenance costs can be minimized. Especially in the field of test automation, AI solutions bring a significant competitive advantage, enabling human testers to focus on the quality and design of the applications and processes of the future.
In this session, we will discuss how AI-driven testing addresses some of today's top test automation challenges. We’ll explore what leaders and organizations need to know when leveraging AI based tools and particularly what’s required to move beyond successful initial pilots to capturing the true value of AI at scale.
Gerta Sheganaku is a Product Manager for AI/ML solutions at Tricentis where she focuses on building AI based tool that enable testers to focus on the fun parts of QA. Previously to joining the Tricentis R&D team, Gerta has worked with customers of various industries and sizes around the globe to develop strategies in making software testing a key enabler for their digital transformation journeys.
Before joining Tricentis, Gerta finished her M.Sc. in Business Informatics at TU Vienna and collaborated with multiple research departments at TU Vienna as well as Data61 (Australia). Her research received multiple awards and focused on operations research and cloud optimization, combining methods from mathematical programming and process management with the latest container-based virtualization technologies. Gerta has also worked as an IT project manager and business process analyst for a software company in Vienna, where she managed cross-organizational R&D projects facilitating data analytics for manufacturing processes.