About the Course
As artificial intelligence and automation rapidly integrate into modern operations, organizations face a critical challenge: adding technology without eliminating underlying complexity simply automates bad processes and makes waste move faster. True transformation requires expanding continuous improvement principles into digital and hybrid work environments.
This course explores how Kaizen evolves in the age of AI, moving from traditional task automation to full process optimization and operating model orchestration. Participants will learn how to identify digital waste, manage a mixed workforce of humans and AI agents, apply the LEAD framework to target high-value friction points, and maintain human-in-the-loop governance to build resilient, scalable systems.
Course Objective
- To understand how Kaizen principles apply to digital workflows, AI integrations, and hybrid operational environments
- To identify new forms of digital waste (digital waiting, overprocessing, and knowledge silos) and transition from task-level quick wins to end-to-end process optimization
- To design and manage a "mixed workforce" connecting human judgment, automation bots, and agentic AI models
- To apply the LEAD framework (Locate, Enhance, Augment, Design) to drive sustainable, value-driven continuous improvement
Course Outline
- The Evolution of Kaizen in the Digital Era- The Paradox of Transformation: Why automating broken processes accelerates operational waste
- Transitioning from physical Gemba walks to digital Gemba observations across systems and prompts
- Identifying and Eliminating Digital Waste- Recognizing digital forms of Muda: Digital motion, overprocessing, stale data decision defects, and isolated knowledge traps
- Evolving standard operating procedures into continuous learning loops
- Designing and Orchestrating a Mixed Workforce- Structuring collaboration between human professionals, rule-driven bots, and agentic AI models
- Defining clear roles: When to delegate to digital agents vs. when human empathy, ethics, and exception-handling are required
- The Three Levels of AI Operational Maturity- Level 1: Task Optimization (individual quick wins and productivity drafting)
- Level 2: Process Optimization (redesigning value stream handoffs and cycle times)
- Level 3: Operating Model Transformation (predictive, event-driven, and context-aware service delivery)
- The LEAD Framework for AI-Driven Continuous Improvement- Locate value and friction points
- Enhance and simplify process flows before applying technology
- Augment with appropriate AI tools and model architectures
- Design for trust, human oversight, feedback loops, and enterprise scale
Target Participants
This course is designed for:
- Continuous improvement practitioners, Lean Six Sigma leads, and operational excellence managers
- Industrial engineers, process analysts, and systems transformation leaders
- Department heads, operations managers, and business unit leaders integrating AI into daily workflows
- Digital transformation consultants, project managers, and innovation champions
Certificate Requirements
- Completion of recorded webinar + quiz
- Pass the 10-item multiple choice with 80% mark
- Comment your feedback on the main page of the course
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