Contracts for acquiring AI in the era of rapid adoption
Organizations and government agencies are acquiring AI at unprecedented speed, often faster than legal, procurement and governance frameworks can adapt. Standard software contracts are pushed beyond their limits, exposing buyers to unclear ownership of outcomes, weak data rights, opaque model behavior, regulatory uncertainty, and misaligned risk allocation.
This panel examines how AI acquisition contracts are structured in practice and where they fail. Panelists will discuss data and training rights, ownership and use of results, audit and transparency provisions, allocation of responsibilities, compensation and performance commitments in an environment where models are continually evolving and legal standards are still forming.
The conversation will also discuss contracting strategies for different acquisition models (SaaS, model licensing, custom development, embedded AI, and government procurement) as well as the growing role of federal agencies and regulators in shaping contract terms. Panelists will explore how organizations can move beyond boilerplate to implement governance-ready contracts that anticipate downstream compliance obligations, security risks, and intellectual property disputes.
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01/28/2026 10:56 p.m.
America/New_York
Contracts for acquiring AI in the era of rapid adoption
Organizations and government agencies are acquiring AI at unprecedented speed, often faster than legal, procurement and governance frameworks can adapt. Standard software contracts are pushed beyond their limits, exposing buyers to unclear ownership of outcomes, weak data rights, opaque model behavior, regulatory uncertainty, and misaligned risk allocation. This panel examines how AI acquisition contracts are structured in practice…
