AI+ Supply Chain Practitioner™
AP-710
Formerly known as AI+ Supply Chain™ <br> <br> Transforming Supply Chain Management- Comprehensive Learning: Covers logistics, operations, and supply chain digitization
- Advanced Supply Strategies: Develop innovative supply strategies and workflows
- Sector-Specific Solutions: Tailored sessions for real-world, sector-specific challenges
- Lead AI Supply Efficiency: Prepares learners to lead in AI-led supply chain efficiency
Why This Certification Matters
Comprehensive Learning: Covers logistics, operations, and supply chain digitization
Advanced Supply Strategies: Develop innovative supply strategies and workflows
Sector-Specific Solutions: Tailored sessions for real-world, sector-specific challenges
Lead AI Supply Efficiency: Prepares learners to lead in AI-led supply chain efficiency
At a Glance: Course + Exam Overview
Program Name
AI+ Supply Chain Practitioner™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Prerequisites
Foundational knowledge of supply chain, Prior experience with business management or technical tools, such as ERP systems or data analysis software, will be beneficial.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Job Roles & Industry Outlook
Supply Chain Manager
Customer Service Professionals
Sales Specialist
Leverage AI tools to improve lead scoring, sales forecasting, and customer engagement.
Digital Marketing Specialist
Design and execute AI-powered marketing campaigns that personalize customer journeys, optimize targeting, and maximize ROI.
Business Intelligence Analyst
Transform data into actionable insights by applying AI-driven analytics to guide smarter business decisions.
Customer Experience Strategist
Harness AI to personalize customer journeys, automate support, and create seamless experiences that drive loyalty.
Industry Growth: AI+ Supply Chain Practitioner™
- Leverage AI for Smarter Supply Chain Operations: Learn how AI tools can optimize logistics, reduce costs, and improve supply chain efficiency from end to end.
- Optimize Demand Forecasting with AI: Use AI-driven analytics to predict demand, streamline inventory management, and reduce stockouts or overstocking.
- Stay Ahead in AI-Powered Supply Chain: As industries increasingly adopt AI, professionals with AI supply chain expertise are in high demand to drive innovation and efficiency.
- Enhance Decision-Making with Predictive Analytics: Master AI algorithms to analyze supply chain data and make informed, real-time decisions to improve overall operations.
Who Should Enroll?
- Supply Chain Professionals: Enhance your supply chain management skills by integrating AI tools for improved forecasting, inventory management, and process optimization.
- Logistics & Operations Managers: Learn to leverage AI for optimizing logistics, route planning, and warehouse management to enhance operational efficiency and reduce costs.
- Procurement Experts: Use AI to improve supplier selection, demand forecasting, and inventory replenishment, streamlining procurement processes.
- Business Leaders: Drive innovation in your supply chain by adopting AI technologies to automate workflows, predict demand, and optimize end-to-end operations.
- Students & New Graduates: Gain a competitive advantage in the supply chain field by mastering AI tools and techniques that are transforming global logistics and supply chain management.
What You'll Learn
- 1.1 SCOR Model and Core Processes (Plan, Source, Make, Deliver, Return, Enable)
- 1.2 Key Functions: Procurement, Inventory Management, Logistics, Warehousing, Demand Forecasting, Risk, and Resilience
- 1.3 Global Challenges: Volatility, Sustainability, Nearshoring, and ESG
- 1.4 KPIs and Performance Measurement
- 1.5 Activity: Analyze and Map a Real-World Supply Chain
- 2.1 AI/ML Fundamentals – Supervised & Unsupervised Learning, Predictive & Prescriptive Analytics, Optimization, Reinforcement Learning
- 2.2 Key Techniques – Neural Networks, Computer Vision, NLP, Digital Twins, Edge AI
- 2.3 AI Tools for SCM
- 2.4 Data Foundations – IoT, Real-Time Data Pipelines, Data Quality & Governance
- 3.1 LLM/GenAI Fundamentals and Enterprise Integration
- 3.2 Use Cases – Demand Planning Assistance, Contract Analysis, Supplier Communication, Scenario Simulation, Report Generation, Synthetic Data
- 3.3 Chat-Based Copilots for Planners and Knowledge Management
- 3.4 Limitations and Best Practices (Hallucinations, Grounding, Integration)
- 3.5 Tools – Enterprise GPT-like Models, LangChain/LlamaIndex, Amazon Business Assistant, Custom GenAI Workflows
- 4.1 Bias in Forecasting/Procurement, Transparency, and Explainability
- 4.2 Privacy, Security, Regulatory Compliance
- 4.3 Job Displacement, Upskilling, and Human-AI Collaboration
- 4.4 Sustainability & ESG – AI for Ethical Sourcing and Carbon Tracking
- 4.5 Governance Frameworks and Risk Management
- 5.1 Digitization – ERP + SCM Platforms, Cloud Integration, Blockchain for Traceability, APIs
- 5.2 Orchestration – Control Towers, Real-Time Visibility, Data Pipelines, Digital Twins
- 5.3 Intelligent & Smart SCM – Predictive/Prescriptive Analytics, Autonomous Exception Management, Robotics + Computer Vision, Edge AI
- 5.4 Human + AI Collaboration Models
- 6.1 Applications Across Industries
- 6.2 Real-World ROI – Efficiency Gains, Cost Reduction, and Resilience Improvements
- 6.3 Implementation Best Practices
- 6.4 Case Studies from Blue Yonder, Kinaxis, Oracle, and Others
- 7.1 Logistics Policies, Trade Regulations, Tariffs, and Geopolitical Risks
- 7.2 Strategic Network Design: Optimization, Resilience, Nearshoring, and Friendshoring
- 7.3 Sustainable SCM: Circular Economy, Green Logistics, and AI-Driven ESG Reporting
- 7.4 Organizational Transformation and Leadership in AI-Enabled Supply Chains
- 7.5 Case Studies
- 8.1 Agentic AI Concepts: Autonomous Goal-Oriented Agents, Multi-Agent Systems, and Reasoning-Action Loops
- 8.2 Applications: Autonomous Replenishment, Risk Mitigation, Supplier Onboarding, Dynamic Rerouting, and End-to-End Orchestration
- 8.3 Tools & Platforms: Kinaxis Maestro Agents, Oracle AI Agents, Blue Yonder Cognitive Agents, Custom Builds, and Automation Anywhere
- 8.4 Architectures, Guardrails, and Human Oversight
- 8.5 Future Outlook for 2026+: From Copilots to Semi-Autonomous Operations
- 8.6 Capstone Project: Design and Prototype a Multi-Agent Workflow for a Supply Chain
- 8.7 Case Studies
- 1. What Are AI Agents
- 2. What Are AI Agents in Logistics and Supply Chain
- 3. Applications & Trends of AI Agents in Supply Chain
- 4. How Does an AI Agent Work
- 5. Core Characteristics of AI Agents
- 6. Key Advantages of AI Agents in Logistics and Supply Chain
- 7. Types of AI Agent
- 8. Case Studies
- 9. Hands on experiment
Tools You'll Explore
LeewayHertz (ZBrain)
C3.ai
Coupa (LLamasoft)
Zebra (Workcloud Demand Intelligence Suite)
Prerequisites
- Foundational knowledge of supply chain, Prior experience with business management or technical tools, such as ERP systems or data analysis software, will be beneficial.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Fundamental Concepts of Supply Chain Management - 11%
- Module 2: AI Concepts, Techniques, and Tools for SCM - 11%
- Module 3: LLM and Generative AI Applications in SCM - 11%
- Module 4: Ethical Considerations and Responsible AI in SCM - 11%
- Module 5: Supply Chain Digitization, Orchestration, and Intelligent Systems - 11%
- Module 6: Industrial Applications, Case Studies, and Business Value - 11%
- Module 7: Strategic SCM, Logistics Policies, and Sustainability - 11%
- Module 8: Agentic AI and the Future of Autonomous Supply Chains - 11%
- Optional Module: AI Agents in Supply Chain - 12%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.