Negotiating an AI Vendor Agreement: A Practitioner's Guide to Training Rights, Output Ownership, Indemnities, and Model Governance
By Casey Scott McKay ·
This guide negotiates a model agreement and then does the work that actually reduces the risk, which is not the negotiation. It starts by identifying the deployment shape - hosted model, retrieval augmentation, or fine-tuning - because the same contract term means different things in each. It reviews the four definitions that determine what every operative clause reaches, drafts the training restriction to cover fine-tuning, evaluation, abuse monitoring, and human review, and closes the aggregated-data carve-out. It replaces the largely fictional output ownership negotiation with a covenant not to assert and a provenance log, works the indemnity carve-outs that swallow the grant, and maps the subprocessor chain. It then turns to use case gating, the acceptable use policy, human review design, and the standing evaluation suite - which together carry more of the risk than the agreement does.
IP and Technology > Information Technology | Guide | Published 27 May 2025 - Updated 8 March 2026 | Casey Scott McKay - marksy.us
Summary. This guide negotiates a model agreement and then does the work that actually reduces the risk, which is not the negotiation. It starts by identifying the deployment shape — hosted model, retrieval augmentation, or fine-tuning — because the same contract term means different things in each. It reviews the four definitions that determine what every operative clause reaches, drafts the training restriction to cover fine-tuning, evaluation, abuse monitoring, and human review, and closes the aggregated-data carve-out. It replaces the largely fictional output ownership negotiation with a covenant not to assert and a provenance log, works the indemnity carve-outs that swallow the grant, and maps the subprocessor chain. It then turns to use case gating, the acceptable use policy, human review design, and the standing evaluation suite — which together carry more of the risk than the agreement does.
Keywords: deployment shape identification · definitions review · training restriction drafting · aggregated data carve-out · covenant not to assert · provenance logging · indemnity carve-out analysis · training data provenance · model change notice · version pinning · subprocessor mapping · human review disclosure · use case gating · acceptable use policy · human review design · evaluation suite · regulated use track · exit and portability · shadow usage · vendor question set
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