AI for Supply Chain

AI for Supply Chain

Introduction

Supply chains are becoming increasingly complex, global, and data-intensive. Volatile demand, disruptions, sustainability requirements, rising logistics costs, and customer expectations are forcing organisations to move beyond traditional planning tools toward AI-enabled, adaptive supply chains.

Artificial Intelligence (AI), particularly Machine Learning, Large Language Models (LLMs), and Generative AI, is transforming how organisations forecast demand, manage inventory, optimise transportation, monitor suppliers, and respond to disruptions in real time. Today, supply chain professionals, not just data scientists, can directly use AI tools to analyse data, generate insights, summarise operational reports, support decision-making, and improve coordination across functions.

This course provides a practical, business-focused introduction to AI for supply chain professionals. Participants will learn AI fundamentals, understand how AI technologies interconnect, and gain hands-on experience with leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM. The emphasis is on real-world supply chain use cases, responsible AI usage, and measurable operational improvements, without requiring programming skills.

Who Should Attend - This course is designed for working professionals involved in supply chain and logistics, including:

Supply chain managers and planners
Procurement and sourcing professionals
Logistics and transportation managers
Warehouse and distribution managers
Demand planning and inventory teams
Operations and production planners
Sustainability and ESG professionals
Digital transformation and analytics teams
Supply chain leaders and decision-makers

Level & Delivery

Beginner to Intermediate | No prior AI or technical background is required | No coding required.
Duration - 2 days | Mode In-house | Methodology - Instructor-led | Hands-on AI tools | Laptop or Tablet required.
Min 5 pax - Max 16 | Hit Get Proposal for an in-house quote. and share as much details in the comment section i.e: no of pax, learning gaps, etc.

Outcome

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

- Understand core AI concepts and terminology relevant to supply chain management
- Distinguish between AI, Machine Learning, Deep Learning, LLMs, and Generative AI
- Evaluate and select AI tools appropriate for supply chain workflows
- Apply AI tools to demand forecasting, inventory planning, logistics analysis, and reporting
- Use AI responsibly within operational, ethical, and organisational constraints
- Identify high-impact AI use cases across end-to-end supply chain processes
- Contribute to AI adoption and digital transformation initiatives in supply chain organisations

Select to design your own content and request for a customized quotation

No	Topic	Topic Description
1	Understanding AI in Supply Chain	What Artificial Intelligence is and is not Relationship between: Artificial Intelligence Machine Learning Deep Learning Large Language Models Generative AI How AI systems learn from supply chain data Current AI applications in supply chain: demand forecasting and planning inventory optimisation logistics and route optimisation supplier performance monitoring disruption detection and response Strengths and limitations of AI in operational environments
2	AI Tools Landscape for Supply Chain Professionals	Overview of modern AI tools for supply chain: ChatGPT, Gemini, Copilot, Claude Perplexity, Grok, Manus, DeepSeek, Qwen, NotebookLM Understanding differences in: capabilities and reliability structured vs unstructured data handling privacy, data security, and supplier confidentiality Selecting the right AI tool for: demand analysis and reporting procurement documentation and contracts logistics updates and operational summaries Prompt engineering fundamentals for supply chain use cases Hands-On Activities Writing prompts for demand and inventory summaries Analysing shipment delays and exception reports using AI Comparing outputs across multiple AI tools
3	AI for Demand Forecasting, Inventory, and Planning	Using AI to support demand forecasting and scenario planning AI-assisted inventory optimisation and safety stock analysis Identifying demand volatility, seasonality, and risks AI-assisted planning reports for management Using AI with spreadsheets: Excel with Copilot Google Sheets with Gemini Hands-On Activities Generating demand insights using AI tools Drafting planning summaries and recommendations
4	Responsible AI, Data Quality, and Governance in Supply Chain	AI risks in supply chain environments: poor data quality and biased forecasts over-reliance on AI outputs supplier and partner data sensitivity Governance considerations: data ownership and access control auditability and traceability Human-in-the-loop decision-making models Best practices for responsible AI usage in supply chain operations
5	AI for Logistics, Transportation, and Distribution	AI concepts in logistics and transportation planning Analysing delivery performance, routes, and costs with AI AI-assisted carrier and mode selection Supporting exception management and disruption response Hands-On Activities Analysing logistics scenarios using AI tools Drafting transportation performance summaries
6	AI for Procurement, Sourcing, and Supplier Management	AI in procurement and sourcing analytics Supplier performance analysis and risk monitoring AI-assisted contract and spend analysis Sustainability and ESG reporting support using AI Hands-On Activities Analysing supplier performance reports using AI Drafting procurement and sourcing insights
7	AI-Enabled Workflow Automation in Supply Chain	Designing AI-supported workflows across the supply chain: data → analysis → decisions → reports Integrating AI tools into daily supply chain operations Improving coordination between planning, procurement, and logistics Measuring productivity, service level, and cost impact Exercise Designing an AI-supported supply chain workflow
8	AI Strategy for Supply Chain Leaders and Decision-Makers	Identifying high-impact AI opportunities across the supply chain Build vs buy vs partner considerations Developing an AI adoption roadmap for supply chain organisations Establishing AI governance, roles, and responsibilities Preparing supply chain teams for AI-enabled operations Workshop Drafting a high-level AI strategy for a supply chain organisation

Expert

Dr. Mohammed Muayad Abdulrazzaq

Dr. Mohammed Muayad Abdulrazzaq, fondly known as Dr. Obay is an accomplished AI Trainer, Academic Leader, TEDx Speaker, Industry Advisor, and Entrepreneur, internationally recognised for his contributions to Artificial Intelligence education, research, and innovation. Holding a Ph.D. in Artificial Intelligence and bringing over 20 years of experience across the information technology landscape, Dr. Obay’s expertise spans AI, Big Data Science, Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), and Immersive Technologies. As a certified and HRD Corp-accredited trainer, Dr. Obay has trained more than 5,000 professionals, students, and business leaders through highly practical and results- driven programs in Data Science, AI Engineering, Generative AI, and LLMs. His workshops are widely praised for their clarity, relevance, and ability to translate complex AI concepts into real-world business impact. Recently, Dr. Obay was honoured to begin a new chapter as an Industry Advisor at ICMS, contributing to advanced programs and professional certifications in Generative AI, Large Language Models, Google AI & Machine Learning, and Microsoft Azure AI. His advisory role bridges academia and industry by empowering future-ready talent and organisations to thrive in the era of intelligent automation. Recognised for his excellence in AI education and leadership, Dr. Obay serves as an ELITE Fellow at the University of Malaya (UM) — Malaysia’s top-ranked university — and as an Adjunct Associate Professor at Taylor’s University, where he supervises Ph.D. and Master’s students at Taylor’s University and the International Islamic University Malaysia (IIUM). His academic work focuses on applying AI to solve real- world problems while shaping the next generation of innovators. An entrepreneur at heart, he is the Founder of Artificial Intelligence & Coding for All (AIC4ALL) — a global learning platform that equips learners of all ages with essential skills in AI, coding, and data science for IR 4.0 & IR 5.0. He also leads INNOEYETIVE, a digital innovation agency leveraging AI, Big Data, and Immersive Tech to accelerate digital transformation. As a TEDx and international speaker, Dr. Obay has delivered impactful talks and keynotes that demystify AI, inspire innovation, and promote ethical adoption of emerging technologies. His lifelong mission is simple yet powerful — to empower professionals, educators, and leaders worldwide to harness the transformative power of AI for a better, smarter future.