Introduction

In a rapidly evolving business landscape, organizations are increasingly leveraging Artificial Intelligence (AI) to achieve operational excellence and drive continuous improvement. This program is designed by Global Horizon Training Center to empower participants with the knowledge and practical tools needed to integrate AI into operational processes, enhance efficiency, and foster a culture of data-driven decision-making. By the end of this course, participants will understand how to harness AI technologies to identify improvement opportunities, automate workflows, and sustain long-term operational success.

Objectives

By the end of this program, participants will be able to:

• Understand the fundamentals of operational excellence and AI.

• Recognize the impact of AI in driving continuous improvement within operations.

• Collect, analyze, and leverage data for operational decision-making.

• Utilize AI tools and techniques for process optimization and automation.

• Develop strategies for implementing and sustaining AI-driven improvement initiatives.

Target Audience

• Operations Managers and Team Leaders

• Continuous Improvement Professionals

• Process Excellence & Quality Assurance Specialists

• Data Analysts and Digital Transformation Officers

• Anyone involved in operational innovation or AI-driven projects

Outlines

Day 1:

Introduction to Operational Excellence and AI Fundamentals

• The principles of operational excellence

• Overview of artificial intelligence: terminology and capabilities

• How AI is transforming operational models

• Case studies: real-world examples of AI in operations

Day 2:

Data-Driven Decision Making for Continuous Improvement

• The critical role of data in operations and improvement

• Best practices for data collection and preparation for AI

• Using AI tools for real-time process monitoring and analytics

• Ensuring data governance and quality in operations

Day 3:

AI Tools and Techniques for Process Optimization

• Introduction to machine learning and predictive analytics

• Applying AI-powered process automation (RPA, intelligent bots)

• Identifying and eliminating process inefficiencies using AI

• Industry use cases: manufacturing, logistics, and services

Day 4:

Implementing AI-Driven Continuous Improvement Initiatives

• Roadmap for integrating AI into existing improvement programs

• Change management strategies for AI adoption

• Overcoming challenges and mitigating risks in AI projects

• Tracking, measuring, and sustaining improvements with AI

Day 5:

Innovation, Future Trends, and Action Planning

• Latest trends and future outlook for AI in operations

• Building a culture of continuous improvement with AI

• Developing actionable plans for AI-powered improvement in your organization

• Group discussion and knowledge sharing: lessons learned and next steps