Augmented Kaizen and AI Root Cause Analysis

Transform continuous improvement with AI-powered Kaizen and root cause analysis. This course is designed for learners who want to use artificial intelligence and machine learning to detect waste, uncover operational causes, prevent failures, and scale measurable improvements. You’ll explore digital GEMBA, process mining, dynamic value stream mapping, anomaly detection, causal analysis, computer vision, and natural language processing for faster, evidence-based root cause analysis. You’ll also examine IoT sensors, edge computing, digital twins, reinforcement learning, and AI-enhanced PDCA for scalable process optimization. Learn how explainable AI, data governance, ethics, workforce trust, and human oversight support responsible implementation. Applications across manufacturing, healthcare, supply chains, financial services, and IT show how AI-enabled continuous improvement can reduce downtime, streamline workflows, improve sustainability, and support successful change. By the end, you’ll be able to evaluate AI-powered improvement technologies, identify anomalies and root causes, and design sustainable, human-centered continuous improvement systems.