Enterprise AI MSA Playbook — Chapter Guide

Ten chapters covering the seven battlegrounds of enterprise AI procurement — from definitions that decide everything to the exit clause that retrieves your operational memory.

  1. Chapter 3

    The Pilot-to-Production Bridge

    Most AI pilot agreements lack the hooks needed for production. Learn how to negotiate the full production MSA up front and use a Pilot Schedule to defer operational carve-outs until graduation.

  2. Battleground 1

    AI Definitions

    The definitions battleground decides ownership, training rights, and data exit. Learn how to define Customer Data functionally — covering vector embeddings, inference logs, and retrieval indices — before the redline finds the gap.

  3. Battleground 2

    Reps, Warranties & AI Accountability

    Standard SaaS warranties fail for AI products. Learn how governance-anchored warranties shift the target from output accuracy to the program that produces outputs — and why this is how enterprise AI deals close.

  4. Battleground 3

    Risk Allocation

    Standard AI vendor contracts cap liability at 12 months of fees with no floor and no output indemnification. Learn the three components of AI-native risk allocation: output indemnification, dollar floors, and a separate super-cap for data breaches.

  5. Battleground 4

    SLAs: Model Availability, Output Quality & Token Latency

    Standard SaaS uptime SLAs do not cover model availability, output quality, or token latency. Learn how to draft a two-tier AI SLA that measures the model, not just the wrapper around it.

  6. Battleground 5

    Security: ZDR, Sub-Processors & AI-Specific Controls

    SOC 2 and ISO 27001 stop at the application layer. Learn the five components of an AI security schedule: ZDR verification, sub-processor disclosure, AI-specific controls, forensic investigation, and governance framework alignment.

  7. Battleground 6

    IP, Licensing & Feedback Loops

    In an AI deal, IP is the first thing that breaks. Learn how to handle output ownership, close the derivative data gap, require training prohibition flowdown, and neutralize the feedback trap.

  8. Battleground 7

    Termination & Exit

    In AI SaaS, termination means retrieving the operational memory of your business — not just the files you uploaded. Learn how to cover data return scope, AI-specific termination triggers, and deletion certification.

  9. Chapter 12

    The Regulatory Overlay

    AI procurement contracts must navigate a moving regulatory target. Learn how the EU AI Act, PIPEDA, Quebec Law 25, Colorado SB24-205, and the AIDA trajectory connect to each battleground clause in your AI MSA.

  10. Chapter 13

    The AI-Native Redline Workflow

    Most enterprise AI deals do not die in the last mile. They die in the first 72 hours. Learn the AI-native redline workflow: triage to the three to five battlegrounds that move the needle, pre-position fallbacks, and close faster.

Content drawn from the Enterprise AI MSA Playbook (June 2026) by Laith Sarhan, Sarhan Data Law. Educational content only — not legal advice.