Becoming an AI-Native Testing Organization

AI is changing how software is designed, built, and validated. As industries transition to AI-native product development, testing organizations must adapt their practices and skills. Manual testing is no longer enough; traditional automation should be enhanced with AI-driven quality engineering, autonomous agents, and data-powered tactics for faster and more reliable product delivery. Join Adam Auerbach to explore what it means to become an AI-Native Testing Organization. He will outline the AI-native software development lifecycle (SDLC) and highlight necessary changes in quality engineering. You’ll learn to assess your current capabilities, identify gaps, and develop a roadmap for modernization. Key topics include: AI-assisted test design and optimization, using AI copilots and autonomous agents to enhance testing, predictive insights through AI-driven risk modeling, synthetic test data generation for improved coverage, strategies for modern testing environments through virtualization and automation, continuous quality enablement in AI-accelerated cycles, governance and standards for responsible AI adoption, and new roles, skills, and career paths within AI-native testing. This session will provide a clear understanding of your current testing organization and a practical plan to evolve into an AI-native quality capability, ensuring your teams are prepared to thrive in the evolving landscape of software engineering.