The legal hub references an AI governance framework as one of the linked customer documents, indicating Snowflake maintains a disclosed framework governing AI-related technology commitments.
This analysis describes what Snowflake'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 existence of a referenced AI governance framework is relevant to customers using Snowflake's AI or machine learning features, as it may define how AI outputs, data used for model training, and related obligations are governed.
Interpretive note: The AI governance framework is referenced but not reproduced in the provided document text; its specific terms, scope, and obligations cannot be assessed.
Customers using Snowflake's AI or ML capabilities should retrieve and review the AI governance framework document linked from this hub, as it may contain terms specific to AI-processed data, model outputs, and associated responsibilities that differ from standard service terms.
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Only models with a post-mitigation score of "medium" or below can be deployed. Only models with a post-mitigation score of "high" or below can be developed further.
ISO/IEC 42001:2023
When you use AI features of the Services, you acknowledge that your inputs may be processed by third-party AI providers. ClickUp may use anonymized and aggregated data derived from your use of the Services to improve and train AI models and features.
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(1) REGULATORY LANDSCAPE: AI governance frameworks may engage the EU AI Act for EU-based deployments, as well as emerging US federal and state-level AI guidance from the FTC and NIST. The specific regulatory obligations depend on the content of the linked AI governance document, which was not available in the provided text. (2) GOVERNANCE EXPOSURE: Medium. The reference to an AI governance framework creates a due diligence trigger for enterprise customers, particularly those in regulated industries where AI use in data processing may require additional contractual or compliance assessments. (3) JURISDICTION FLAGS: EU/EEA customers should assess whether the AI governance framework aligns with EU AI Act risk classifications applicable to their use cases. US customers in financial services or healthcare should assess AI governance terms against sector-specific guidance. (4) CONTRACT AND VENDOR IMPLICATIONS: Enterprise procurement teams should request the AI governance framework as part of vendor due diligence and assess whether it allocates responsibility for AI output accuracy, bias, or regulatory compliance between Snowflake and the customer. (5) COMPLIANCE CONSIDERATIONS: Compliance teams should review the AI governance framework document to determine whether it imposes any obligations on customers regarding how they deploy AI features, what data they may use as inputs, and what disclosures may be required to their own end users.
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How 10 AI platforms describe the use of user data for model training, improvement, and development, based on archived governance provisions.
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The existence of a referenced AI governance framework is relevant to customers using Snowflake's AI or machine learning features, as it may define how AI outputs, data used for model training, and related obligations are governed.
Customers using Snowflake's AI or ML capabilities should retrieve and review the AI governance framework document linked from this hub, as it may contain terms specific to AI-processed data, model outputs, and associated responsibilities that differ from standard service terms.
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