Laboratory medicine is shifting beyond traditional automation into an era of intelligent AI-driven augmentation. AI is transforming analytical workflows from standardized, linear processes into adaptive, predictive systems that actively support clinical decisions. These technologies enhance quality management, improve diagnostic accuracy, and facilitate earlier and more accurate interpretation across various disciplines. As laboratories become data-driven ecosystems, professionals move from operating instruments to overseeing algorithmic performance, validating digital tools, and collaborating with clinicians to deliver patient-centred diagnostics. This evolution also brings critical challenges, including data integrity, algorithmic transparency, ethical governance, and new regulatory and cybersecurity demands. Understanding how AI will reshape workflows, competencies, and responsibilities is essential for laboratories aiming to remain resilient and competitive. This questionnaire examines the opportunities and constraints that define the transition from automation to proper augmentation.