Same Service, Different Model: Managing AI Model Changes in Technology Agreements

A company licenses an artificial intelligence–enabled service after evaluating its functionality, security, performance, and compliance characteristics. Six months later, the provider upgrades the underlying model or replaces it altogether. The product may look the same, but the technology beneath it may have changed in ways that affect performance, data processing, regulatory compliance, or the customer’s downstream obligations.

Model changes are increasingly part of the artificial intelligence (AI) lifecycle. Developers release new models and retire older ones, and providers that rely on those models may need to migrate. For both sides of an AI transaction, this raises a practical question: What happens when the model evaluated at signing is not the model in use during the term?

Technology agreements have traditionally given providers broad flexibility to update and improve their services, and providers have legitimate reasons to preserve such mutability. Customers, meanwhile, may care about the specific model where it is a material component of the solution.

Routine patches, security updates, and improvements that do not materially affect the service may remain within the provider’s discretion. Other changes may warrant a different process, such as replacing a foundation model, changing the third-party model provider, adding new capabilities, or materially altering performance or the handling of customer data. The parties may wish to define where that line falls.