In this session, we will explore the concept of model drift in AI and its impact on the accuracy and reliability of AI systems. You'll learn about the different types of model drift, including concept drift, covariate drift, prior probability drift, instance drift, and label drift. You'll also see real-life examples of model drift in AI and learn about techniques for detecting and mitigating drift in AI systems. You will gain insights into the practical steps that organizations can take to stay ahead of the curve and manage model drift in AI. Whether you're a data scientist, AI developer, or business leader, this session will equip you with the knowledge and strategies you need to address model drift and ensure the reliability of your AI systems.