The correct option is Google Cloud's enterprise data isolation policy that states customer data from services like Vertex AI is not used to train Google's general foundation models.

This policy is the explicit commitment that customer data used for training and prediction in Vertex AI remains isolated and is not used to train Google's general purpose models. It covers prompts, inputs, training datasets and outputs, and it applies by default unless a customer chooses to share data for improvement. This is the only choice that directly addresses the executives' requirement for a data usage guarantee.

Customer-managed encryption keys protect data confidentiality by allowing you to control encryption at rest, yet encryption does not determine whether Google can use your content for model training. It is a security control rather than a data usage commitment, so it does not provide the required guarantee.

Cloud TPUs are hardware accelerators that improve performance for training and inference. They do not establish data governance or usage restrictions, so they do not meet the requirement.

Automatic scaling on Vertex AI adjusts infrastructure capacity to handle variable workloads. This is an operational feature and not a policy about how data may be used, so it does not satisfy the confidentiality assurance the executives require.

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