Course Overview
Generative AI Awareness for Supply Chain & Support Functions
This Generative AI Training program is designed to help manufacturing professionals understand how Generative AI can enhance operational efficiency, decision-making, collaboration, and continuous improvement across supply chain and support functions. The training introduces practical Gen AI concepts, tools, risks, and use cases relevant to supply chain-manufacturing environments, including HR & Finance-Cost Control, Maintenance & Safety, QA, Inventory & Warehousing, Logistics, and Continuous Improvement. Through interactive discussions, demonstrations, and hands-on group activities, participants will explore how Gen AI can support productivity, problem-solving, reporting, analysis, and operational excellence initiatives.
This AI for Supply Chain Training combines practical demonstrations, real manufacturing examples, and collaborative activities to help participants confidently explore AI adoption.
Course Objectives
- Build foundational awareness of Generative AI concepts and capabilities.
- Understand how Gen AI applies across manufacturing and supply chain operations.
- Identify practical use cases for different business functions.
- Learn responsible and secure use of Gen AI in enterprise environments.
- Explore how Gen AI supports productivity, decision-making, and continuous improvement.
- Encourage cross-functional collaboration and AI adoption readiness.
Learning Outcomes
Throughout this Manufacturing AI Training, participants will gain practical knowledge that can be applied across different manufacturing and business support functions, participants will be able to:
- Explain the basics of Generative AI and common AI terminology.
- Recognize opportunities to apply Gen AI within their daily work.
- Use effective prompting techniques for business tasks.
- Identify risks, limitations, and governance considerations.
- Collaborate to design practical Gen AI use cases for manufacturing operations.
- Develop initial ideas for responsible AI adoption within their departments.
Who Should Attend
- Supply Chain & Procurement Teams
- HR & Finance / Cost Control Personnel
- Maintenance & Safety Teams / Quality Assurance & Compliance Teams
- Inventory & Warehousing Personnel / Logistics & Distribution Teams
- Continuous Improvement / Operational Excellence Teams
- Manufacturing Supervisors and Managers / Business Support Functions
Course Content
Day 01 Agenda – Foundations & Manufacturing Use Cases
| Schedule | Topic | Subtopics |
| 0900 – 0930 | Ice Breaker & Program Introduction | Participant introductions; AI expectations survey; Manufacturing challenges discussion; Training objectives and agenda overview |
| 0930 – 1000 | Introduction to Generative AI | What is Gen AI; AI vs Automation vs Analytics; How Gen AI works; Current trends in manufacturing |
| 1000 – 1030 | Gen AI Tools & Capabilities | Text, image, document, and data generation; Chatbots and copilots; Examples of enterprise AI tools |
| 1030 – 1045 | Morning Break | Refreshments and networking |
| 1045 – 1115 | Prompting Fundamentals | Effective prompting techniques; Prompt structure; Improving AI responses; Common prompting mistakes |
| 1115 – 1145 | Gen AI for Supply Chain Operations | Demand planning support; Supplier communication; Procurement assistance; Forecasting insights |
| 1145 – 1215 | Gen AI for Inventory & Warehousing | Inventory reporting; Stock analysis; Warehouse documentation; Cycle count support |
| 1215 – 1315 | Lunch Break | Lunch |
| 1315 – 1415 | Group Activity 1: Manufacturing Use Case Discovery | Teams identify operational pain points; Brainstorm AI opportunities; Map AI benefits to departments; Present findings |
| 1415 – 1445 | Gen AI for Logistics & Distribution | Shipment coordination; Delivery communication; Route optimization support; Logistics reporting |
| 1445 – 1515 | Gen AI for HR & Finance-Cost Control | HR policy drafting; Recruitment support; Budget analysis summaries; Cost reporting assistance |
| 1515 – 1530 | Afternoon Break | Refreshments and networking |
| 1530 – 1600 | Responsible AI & Governance | Data privacy; Security considerations; Hallucinations and bias; Human oversight |
| 1600 – 1630 | Group Activity 2: Prompt Engineering Challenge | Teams create prompts for manufacturing scenarios; Compare AI outputs; Discuss best practices |
| 1630 – 1700 | Wrap Up & Q&A | Day 1 reflection; Key learning points; Open discussion and questions |
Day 02 Agenda – Functional Applications & Adoption Readiness
| Schedule | Topic | Subtopics |
| 0900 – 0930 | Day 01 Recap & Reflection | Key lessons review; Participant sharing; Clarification of concepts; Day 2 overview |
| 0930 – 1000 | Gen AI for Maintenance Operations | Maintenance troubleshooting support; SOP generation; Work order summaries; Predictive maintenance concepts |
| 1000 – 1030 | Gen AI for Safety Management | Incident reporting; Safety communication; Toolbox talk generation; Compliance support |
| 1030 – 1045 | Morning Break | Refreshments and networking |
| 1045 – 1115 | Gen AI for Quality Assurance (QA) | Audit preparation; CAPA documentation; Quality reporting; Root cause analysis support |
| 1115 – 1145 | Gen AI for Continuous Improvement | Lean and Kaizen support; Problem-solving frameworks; Report automation; Improvement idea generation |
| 1145 – 1215 | AI-Enhanced Decision Making | Data summarization; Trend analysis; Executive reporting; Scenario-based recommendations |
| 1215 – 1315 | Lunch Break | Lunch |
| 1315 – 1345 | AI Risks, Ethics & Workforce Readiness | Ethical AI usage; Change management; Employee adoption; Governance and accountability |
| 1345 – 1415 | Future of AI in Manufacturing | Smart factories; AI-enabled operations; Human + AI collaboration; Emerging trends |
| 1415 – 1445 | AI-Enhanced Decision Making | Data summarization; Trend analysis; Executive reporting; Scenario-based recommendations |
| 1445 – 1515 | Building an AI Adoption Roadmap | Identifying quick wins; Prioritization framework; Stakeholder engagement; Pilot project ideas |
| 1515 – 1530 | Afternoon Break | Refreshments and networking |
| 1530 – 1630 | Group Activity 3: Department AI Action Plan | Teams create departmental AI action plans; Adoption priorities; Success measures; Presentation and feedback |
| 1630 – 1700 | Wrap Up, Q&A & Next Steps | Final reflections; Questions and answers; Key takeaways; Recommended next actions |
Upon completion of this Generative AI Training, participants will be able to identify AI opportunities, improve operational productivity, and support responsible AI adoption within their departments.
