Programme overview
Technical depth: Conceptual · Practical mode: Case study
Introduction
Every AI initiative now begins with a sourcing choice: build on internal talent, buy a packaged product, subscribe to a foundation model or partner with a specialist. Choices made quickly on demonstrations and list prices often lock organisations into opaque models, rising usage fees, weak data protections and contracts with no exit. This Core Concept course equips executives to frame the build-versus-buy decision, run a disciplined AI vendor evaluation and negotiate the terms that protect data, performance and future options. Participants leave with an AI Sourcing Decision Paper for a live AI need in their organisation.
Course Objectives
- Frame an AI sourcing decision by comparing build, buy, subscribe and partner options against strategic, capability and cost criteria
- Direct an AI vendor evaluation using weighted criteria, proof-of-concept tests and structured due diligence evidence
- Assess vendor claims on model performance, training data, security and responsible AI practice before contract award
- Negotiate AI contract terms covering data use, intellectual property, service levels, liability and model change
- Plan for vendor lock-in, concentration risk and exit so that the organisation keeps its options open
- Present an AI Sourcing Decision Paper that a board or investment committee can approve
Target Audience
- Executives who sponsor AI initiatives and approve the sourcing route for them
- Technology and digital executives accountable for enterprise architecture and platform choices
- Procurement and commercial executives responsible for strategic technology contracts
- Finance executives who approve AI spend and long-term subscription commitments
- Legal, risk and compliance executives who sign off data, intellectual property and liability terms
Course Outline
Day 1: The AI Sourcing Landscape
- AI Supply Market Map: Foundation Models, Platforms, Packaged Applications and Integrators
- Sourcing Options: Build, Buy, Subscribe, Fine-Tune and Partner
- Kraljic Matrix Positioning of AI Purchases
- Current AI Supplier Inventory and Shadow AI Spend Review
- Strategic Differentiation Test for Which AI Capabilities to Own
Day 2: Decision and Procurement Frameworks
- Build-Versus-Buy Decision Matrix: Capability, Speed, Control and Cost
- WEF Guidelines for Procurement of AI Solutions and AI Procurement in a Box
- ISO/IEC 42001 Annex A Controls for Suppliers and Third-Party AI
- ISO/IEC 27036 Supplier Relationship Security Requirements
- AI Total Cost of Ownership Model Across Five Years
Day 3: Evaluating AI Vendors
- Weighted Vendor Evaluation Scorecard Design
- Proof-of-Concept Design With Task-Specific Evaluation Sets
- Model Cards, SOC 2 Reports and Security Questionnaires as Due Diligence Evidence
- Responsible AI Review of Vendors Using the NIST AI RMF Functions
- Reference Checks and Vendor Financial Viability Assessment
Day 4: Contract Risk, Lock-In and Exit
- Data Use, Retention and Model Training Clauses
- Intellectual Property Ownership of Prompts, Outputs and Fine-Tuned Models
- Service Levels for Accuracy, Latency, Availability and Model Version Change
- Vendor Lock-In, Concentration Risk and Multi-Model Architecture Options
- Exit Plans, Data Portability and Transition Assistance Terms
Day 5: Case Work and the Sourcing Decision Paper
- Insurance Claims Automation Case Study: Build or Buy Recommendation
- Retail Generative AI Assistant Case Study: Vendor Shortlist Evaluation
- Contract Term Sheet Negotiation Exercise
- AI Sourcing Decision Paper Drafting for an Own AI Need
- Investment Committee Panel and Decision Defence
Skills You Will Gain
- AI Sourcing Strategy
- Build-Versus-Buy Analysis
- AI Vendor Due Diligence
- Supplier Evaluation Design
- AI Contract Negotiation
- Third-Party AI Risk Management
- Lock-In and Exit Planning
- Technology Investment Decision-Making
Why Attend This Course
- Return to work with an AI Sourcing Decision Paper for a real AI need, tested before an investment panel
- Look past vendor demonstrations to the evidence that shows whether a product will perform on your own data
- Recognise the contract terms that decide who owns your data, outputs and future options
- Compare sourcing experience with executives from banking, insurance, retail, energy and government
Conclusion
The way an organisation sources AI shapes its costs, risks and room to manoeuvre for years after the contract is signed. This course moves from the AI supply market and sourcing options, through build-versus-buy and procurement frameworks, to vendor due diligence, contract terms and exit planning. The final day turns that material into an AI Sourcing Decision Paper that executives take back to their investment committee, giving them a structured and defensible basis for their next AI purchase or build.