AI Vendor Management
A 50-minute working session for procurement, VMOs, and IT sourcing — running AI vendors with the same discipline as any other critical supplier.
Last updated: 2026-05-19
What you'll learn
By the end of this course you'll be able to:
- The AI vendor landscape — hyperscalers, ISVs, boutiques, SI partners, and where each one actually adds value
- A diligence checklist built for AI specifically — not the generic SaaS template
- Contract terms that matter — IP, data, model risk, sub-processors, training-use
- Performance SLAs that mean something for AI services (latency, accuracy, drift)
- Lock-in mitigation — open weights, data portability, prompt portability, escrow
- Vendor offboarding — the conversation nobody plans for and everyone needs
Who this is for
Chief procurement officers, vendor management office leads, IT sourcing leaders, category managers for technology, and contracts directors. Especially valuable for VMOs at BFSI, healthcare, telco, and large public-sector buyers across the GCC and India who now have AI sitting across half of their software renewals and need a consistent way to diligence, contract, and exit AI vendors.
Curriculum
7 chapters · 2 hands-on exercises · capstone challenge
Each chapter ends with the learning objectives ticked off. Quizzes are auto-graded with feedback; exercises are open-ended and produce artifacts you can take to your team.
1. The AI vendor landscape
- Distinguish hyperscaler, ISV, boutique, and SI value propositions
- Recognize the 3 vendor archetypes most likely to over-promise on AI
2. Diligence checklist for AI vendors
- Apply a 12-item AI-specific diligence checklist before signing
- Spot the diligence answers that are red flags vs. routine
3. Contract terms — IP, data, model risk, sub-processors
- Negotiate the 6 AI-specific clauses most standard MSAs are missing
- Pin down sub-processor disclosure and training-data-use commitments
4. Performance SLAs that mean something
- Set SLAs across latency, availability, accuracy, and drift
- Avoid the "uptime-only SLA" trap that ignores model behavior
5. Lock-in mitigation
- Apply 4 lock-in tests — model, data, prompt, integration
- Use open weights, portability commitments, and escrow where they're realistic
6. Vendor offboarding — the conversation nobody plans
- Pre-write the offboarding plan at signing, not at termination
- Identify the 3 offboarding risks unique to AI (data deletion proof, model retention, retraining echoes)
Capstone: Capstone: Your AI vendor playbook
- Draft a 1-page AI vendor diligence and contract playbook your category team can apply
- Define the tiering rule that decides which AI vendors get the full treatment
Capstone deliverable: Every learner who completes this course produces «Your 1-Page AI Vendor Playbook» — a tangible artifact you take back to your organization.
Curriculum live · full chapter content rolling out through 2026.
The outline, learning objectives, references, and capstone deliverable are published. Full chapter content (video, narration, exercises) ships progressively. Get notified when each chapter goes live.
References & sources
Built on cited sources — not vibes.
Every course is researched fresh against vendor documentation, regulatory sources, and peer-reviewed work. Sources used in this course:
NIST AI Risk Management Framework
National Institute of Standards and Technology · Source link
EU AI Act — Final Text
European Parliament · Source link
OECD AI Principles
OECD · Source link
Gartner — Sourcing and Vendor Management research
Gartner · Source link
SAMA — Outsourcing Regulations
Saudi Central Bank · Source link
Course details
Track
Leadership
Level
Intermediate
Audience
Manager, Director, Executive
Industry
Cross-Industry
Stack
Stack-agnostic
Paired Gennoor Way phase
diagnose, sustain
Format
reading, video
You finished the course. Now what?
From course to outcome.
Reading this course is step one. The next step is applying it where you work. Here's how Gennoor helps — without the deck, without the pitch.
Run this for your team
A 2-day workshop or virtual cohort for up to 25 of your people, with exercises run on your data and a 30-day adoption plan.
From $5k · 2 weeks · function-specific
Apply this to your data
A 4–6 week pilot that takes what you learned and ships a working system inside your environment. Fixed scope, fixed price, code transferred day one.
From $25k · 6 weeks · production-grade
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