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Generative AI for Continuous Improvement

Generative AI for Continuous Improvement

1h 1mIntermediate2025-02-18

Authors

Vincent Mirabelli

Vincent Mirabelli

Keynote Speaker | Trainer | Author

Course details

In this course, Vincent Mirabelli—a keynote speaker, trainer, and author—dives into how generative AI can transform your approach to continuous improvement. Learn how to use AI tools to optimize processes, enhance predictive maintenance, streamline quality control, and efficiently analyze customer feedback. Build more informed decision-making through AI in real-time data analysis, automated root cause identification, and process simulations. Explore relevant AI tools and techniques that empower you to make data-driven improvements. Plus, discover the impact of AI on organizational roles and culture, and strategies for managing associated risks. When you complete this course, you will be equipped to use AI-enhanced continuous improvement to drive efficiency, innovation, and competitive advantage within your organization.

Skills covered

Business AnalysisArtificial Intelligence for DesignOperations ManagementAI Productivity ToolsVideoPhotographyProject ManagementGraphic DesignAnimation and IllustrationBusiness Analysis and StrategyBusiness Software and ToolsOne-Off

Concepts

0. Introduction

  • 01 - Power up CI with AI

1. Enhancing CI with AI

  • 02 - What is continuous improvement
  • 03 - How has CI changed with AI
  • 04 - What's possible in CI with AI

2. Tools and Use Cases for AI in CI

  • 05 - Ai tools to use for CI
  • 06 - Automating root cause analysis
  • 07 - Process optimization through simulation
  • 08 - Predictive maintenance
  • 09 - Enhancing customer feedback analysis
  • 10 - Streamlining quality control
  • 11 - Enhanced training and knowledge transfer
  • 12 - Cost reduction and waste minimization
  • 13 - Personalizing continuous improvement programs

3. Impact to the Organziation

  • 14 - How does the org change
  • 15 - How risks can be managed
  • 16 - How to oversee your CI program

Conclusion

  • 17 - What does a possible future look like for AI and CI
  • 18 - Next steps

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