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

• Understand how AI enhances traditional supplier selection processes
• Differentiate between rule-based, analytical, and AI-driven supplier evaluation
• Identify key data sources used in AI-based supplier scoring
• Apply AI concepts to:
• Supplier shortlisting
• Risk identification and prioritization
• Continuous supplier monitoring
• Interpret AI-generated supplier risk scores and insights
• Integrate financial, operational, ESG, and geopolitical risk factors
• Improve sourcing decisions while reducing supplier-related disruptions
• Establish governance and controls for responsible AI use in procurement

This course is designed for:

• Procurement and Strategic Sourcing Professionals
• Category and Supplier Relationship Managers
• Supply Chain and Operations Managers

• Risk Management and Business Continuity Teams
• Vendor Management and Outsourcing Professionals
• Digital Transformation and Analytics Leaders
• Compliance, ESG, and Sustainability Professionals
• Managers involved in supplier approval and sourcing decisions

No AI, data science, or programming background is required.

The course uses a practical, decision-oriented, and interactive approach, including:

• Instructor-led conceptual sessions
• Real-world procurement and supply chain case studies
• AI supplier selection and risk scoring use cases
• Group discussions and scenario-based analysis
• Hands-on workshops using simplified supplier datasets
• Visual dashboards and scorecard interpretation
• Group exercises focused on governance and decision-making

Emphasis is on how to use AI insights responsibly, not how to build AI models.

Day 1 – Foundations of AI in Supplier Selection

Topics:

• Evolution of supplier selection:
• Traditional scorecards → Advanced analytics → AI-driven decisions
• Limitations of conventional supplier evaluation models
• Introduction to AI concepts in procurement:
• Machine learning (conceptual)
• Predictive vs prescriptive analytics

• Data sources for AI-based supplier selection:
• Internal performance data
• Financial and credit data
• ESG and compliance data
• Market and geopolitical signals
• Bias, transparency, and explainability in AI decisions
• Role of human judgment vs AI recommendations

Workshop:

• Mapping current supplier selection processes and AI opportunities

Day 2 – AI-Based Supplier Risk Scoring

Topics:

• Understanding supplier risk:
• Financial risk
• Operational risk
• Supply continuity risk
• ESG and reputational risk
• Geopolitical and country risk
• Traditional risk scoring vs AI-driven risk scoring
• Leading vs lagging risk indicators
• Continuous supplier monitoring using AI
• Early-warning signals and risk prediction
• Interpreting supplier risk dashboards and alerts
• Using AI risk scores in sourcing and contracting decisions

Case Study:

• AI-based identification of high-risk suppliers before disruption

Practical Exercise:

• Interpreting multi-factor supplier risk scores and prioritizing actions
  
  

Day 3 – Decision-Making, Governance & Implementation

Topics:

• Integrating AI insights into sourcing decisions:
• Supplier shortlisting
• Award decisions
• Dual sourcing and risk mitigation strategies
• AI in supplier onboarding and approval workflows
• Governance of AI in procurement:
• Accountability and decision rights
• Auditability and compliance
• Ethical, legal, and regulatory considerations
• Common pitfalls and misconceptions of AI in supplier management
• Measuring value from AI-driven supplier selection:
• Risk reduction
• Cost avoidance
• Service continuity
• Building a roadmap for AI-enabled supplier selection and risk management

Final Group Exercise:

• Develop an AI-Based Supplier Selection & Risk Scoring Framework:
• Data inputs
• Risk dimensions
• Decision rules
• Governance controls

CDGA attendance certificate will be issued to all attendees completing minimum of 80% of the total course duration.