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Artificial Intelligence (AI) Supply Chain Certification (AI SCM Pro).

This is our first attempt at a certification program.  It is a work in process.  We would really like to get your constructive criticism to improve it.  Follow this link to the LinkedIn discussion to provide ideas and improvement suggestions. 
Credential: Certified AI Supply Chain Professional (AI SCM Pro)  Price: FREE

Program Purpose:
This certification equips professionals with a clear, practical, and executive-level understanding of where, why, and how to apply Artificial Intelligence across the end-to-end supply chain. Graduates will not become data scientists—but they will know how to identify high-value AI use cases, evaluate vendors, lead AI initiatives, and drive measurable business results.

Target Audience:

  • Supply chain, logistics, procurement, and operations professionals

  • Supply chain leaders evaluating AI investments

  • Analysts, consultants, and transformation leaders

  • Executives who need AI literacy without coding depth

PROGRAM LEARNING OUTCOMES

By the end of this certification, learners will be able to:

  • Identify high-ROI AI opportunities across the supply chain

  • Understand how AI actually works (without math or code)

  • Select the right AI tools and vendors

  • Avoid common AI failure traps

  • Lead AI-enabled supply chain transformations

  • Communicate AI value clearly to executives

 

CERTIFICATION STRUCTURE

MODULE 1: AI Fundamentals for Supply Chain Leaders

Purpose: Build AI literacy without technical overload

MODULE STRUCTURE

  • Lesson 1: What AI Really Is (Using Plain Language)

  • Lesson 2: AI vs Automation vs Analytics (Common Confusion)

  • Lesson 3: Types of AI You’ll See in Supply Chain

  • Lesson 4: How AI Learns – Explained Simply

  • Lesson 5: Real-World Supply Chain Examples of AI

  • Lesson 6: Why AI Projects Fail (And How to Avoid It)

  • Lesson 7: AI Myths, Hype & Red Flags

  • Executive Cheat Sheet

  • Knowledge Check Quiz

Outcome: Speak confidently about AI with technical teams and vendors

MODULE 2: Supply Chain Data Foundations (Critical)

Purpose: Understand why data—not algorithms—is the constraint

Key Topics:

  • Types of supply chain data (master, transactional, external)

  • ERP, WMS, TMS, MES data sources

  • Data quality, latency, and bias

  • Internal vs external data (weather, geopolitics, demand signals)

  • Data governance basics

Outcome: Assess AI readiness of your organization

MODULE 3: AI in Demand Forecasting & Planning

Use Cases:

  • AI-based demand sensing

  • Promotion and seasonality modeling

  • Short-term vs long-term forecasting

  • Forecast accuracy vs bias reduction

AI Techniques:

  • Time-series ML models

  • Ensemble forecasting

  • Probabilistic forecasting

Outcome: Know when AI outperforms traditional forecasting—and when it doesn’t

MODULE 4: AI in Inventory Optimization

Use Cases:

  • Safety stock optimization

  • Multi-echelon inventory planning

  • Service-level optimization

  • Slow-moving & obsolete inventory detection

AI Value:

  • Reduced working capital

  • Higher service levels

Outcome: Apply AI to balance cost, service, and risk

MODULE 5: AI in Procurement & Strategic Sourcing

Use Cases:

  • Spend classification using AI

  • Supplier risk prediction

  • Cost should-be modeling

  • Contract analytics (GenAI)

Outcome: Use AI to improve sourcing decisions and supplier resilience

MODULE 6: AI in Logistics & Transportation

Use Cases:

  • Route optimization

  • ETA prediction

  • Carrier performance scoring

  • Autonomous planning & exception management

Outcome: Improve logistics cost, speed, and reliability

MODULE 7: AI in Manufacturing & Operations

Use Cases:

  • Predictive maintenance

  • Yield optimization

  • Production scheduling

  • Quality inspection (computer vision)

Outcome: Apply AI to improve uptime and throughput

MODULE 8: AI for Supply Chain Risk, Resilience & ESG

Use Cases:

  • Supplier disruption prediction

  • Geopolitical and climate risk modeling

  • Scenario simulation

  • Compliance and ESG monitoring

Outcome: Move from reactive firefighting to proactive risk management

MODULE 9: Building the AI Business Case

Key Topics:

  • Identifying high-ROI use cases

  • Cost vs value modeling

  • KPIs and success metrics

  • Buy vs build decisions

  • Pilot to scale roadmap

Outcome: Justify AI investments to leadership

 

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Supply Chain AI Certification Resources

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