AWS states that it will not use the data or content you send to Bedrock models to train Amazon's own AI models unless you have given consent for that use.
This analysis describes what AWS Bedrock's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
The terms explicitly state that customer prompts and content submitted through Bedrock inference are not used to train Amazon foundation models by default, which is a material data handling commitment relevant to customers submitting proprietary or sensitive data.
Interpretive note: The scope of what constitutes customer content versus aggregated service metadata is not exhaustively defined, creating some uncertainty about the full extent of the no-training commitment.
This change introduces a new optional service feature rather than modifying existing consumer rights or obligations. AWS explicitly disclaims providing regulated financial services, holding custody o…
Organizations submitting proprietary business data, personal data, or sensitive information as prompts through Bedrock can rely on the terms' statement that this content is not used to train Amazon's foundation models by default; however, customers should confirm that their specific Bedrock configuration and any fine-tuning features they use are covered by this commitment.
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"AWS processes Customer Content you submit to Amazon Bedrock in accordance with the AWS Customer Agreement and applicable data protection terms. AWS does not use Customer Content processed by Amazon Bedrock to train Amazon's foundation models without your consent.— Excerpt from AWS Bedrock's AWS Service Terms
(1) REGULATORY LANDSCAPE: This provision directly engages GDPR, CCPA, and HIPAA frameworks where customer content includes personal data or protected health information. The statement that customer content is not used for model training without consent is a material disclosure relevant to data minimization and purpose limitation principles under GDPR. AWS's status as data processor for customer-submitted inference data requires a valid data processing agreement, which customers should confirm is in place. (2) GOVERNANCE EXPOSURE: Medium. The commitment not to use customer content for model training is significant, but the scope of what constitutes customer content versus service metadata, aggregated usage statistics, or anonymized data is not exhaustively defined in this provision, leaving some interpretive uncertainty about what data categories are covered by this commitment. (3) JURISDICTION FLAGS: EU customers have heightened rights under GDPR to confirm the scope of data processing and obtain documentation of the specific processing purposes for customer content submitted to Bedrock. California customers have analogous rights under CCPA regarding the use of personal information. (4) CONTRACT AND VENDOR IMPLICATIONS: Enterprise customers should verify that AWS Data Processing Addenda are current and scoped to cover Bedrock inference endpoints. For healthcare customers, a Business Associate Agreement must be in place before submitting any data that could constitute protected health information. (5) COMPLIANCE CONSIDERATIONS: Data mapping exercises should include Bedrock inference endpoints as data processing touchpoints, documenting the categories of data submitted in prompts and the legal basis for processing under applicable data protection law. Customers using Bedrock fine-tuning features should conduct a separate review of whether fine-tuning data submission is governed by the same no-training commitment.
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The terms explicitly state that customer prompts and content submitted through Bedrock inference are not used to train Amazon foundation models by default, which is a material data handling commitment relevant to customers submitting proprietary or sensitive data.
Organizations submitting proprietary business data, personal data, or sensitive information as prompts through Bedrock can rely on the terms' statement that this content is not used to train Amazon's foundation models by default; however, customers should confirm that their specific Bedrock configuration and any fine-tuning features they use are covered by this commitment.
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