After hearing benefits Generative AI will bring to testing over the last few years, the AI paradigm is evolving to orchestrate complex multi-step processes within automation. The recent introduction of Agentic AI enables the design, thinking, and learning of large-scale, interconnected tasks that require adaptive decision-making and real-time adjustments, enhancing the capabilities of automation workflows. At the same time, organizations are grappling with the operational demands of legacy systems. The shift to dynamic runtime test automation, powered by next-generation technologies such as Large Action Models (xLAM) and Visualization of Thought (UFO), presents both opportunities and challenges. How can quality engineers strike the right balance between adopting cutting-edge solutions and maintaining enterprise-scale automation?

In this keynote, Jonathon will explore how test automation can thrive amidst these dual forces. Drawing on real-world R&D and practical implementations, we will delve into:

– AI-Augmented Testing with Agentic AI: Harnessing Agentic AI to enable adaptive, autonomous decision-making within test automation workflows. Learn how Agentic AI-driven systems can dynamically identify, prioritize, and execute test cases, reducing manual intervention and enhancing testing efficiency.

– Successes, Failures, and Lessons Learned: A candid look at organizations navigating the integration of Agentic AI and other emerging technologies, with real-world case studies showcasing the journey from experimentation to impactful results.

– Sustainable Automation: Balancing speed, scalability, and maintainability to future-proof your automation investments. Explore how Agentic AI fosters sustainability by continuously optimizing resources and refining testing processes in real time.