This provision establishes that enabling specific product features, including Einstein and Agentforce capabilities, triggers the activation of additional infrastructure providers and sub-processors beyond those used for the base service, with Customer Data processed by those additional entities and locations as a consequence of feature enablement.
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This provision creates a direct operational link between feature configuration decisions and sub-processor inventory: enabling Einstein NLP, generative AI, speech, or analytics features introduces additional sub-processors including AWS, Microsoft Azure, OpenAI, Deepgram, LiveKit, and Eleven Labs across multiple jurisdictions, requiring that organizations maintain a dynamic sub-processor map that reflects their current feature configuration.
Under this clause, the set of sub-processors processing Customer Data is not static but expands as additional features are enabled within covered services. The document states that if these features are enabled, Customer Data will be processed by the additional infrastructures, making feature activation decisions a direct determinant of the applicable sub-processor chain.
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"Some Services run primarily on one infrastructure, but have some features that run partly or entirely on different infrastructures. For example, for many Customers, most Sales Cloud features run on the Salesforce's first-party infrastructure, but Sales Cloud also includes Einstein1 Features that run on the Einstein Platform infrastructure. Similarly, the Marketing Cloud Engagement Services are based primarily on the Marketing Cloud Engagement infrastructure, but some features of Marketing Cloud run partially on Einstein Platform or Marketing Cloud Einstein infrastructure. If these features are enabled, Customer Data will be processed by these additional infrastructures.— Excerpt from Slack's Slack Sub-Processors (Salesforce)
(1) REGULATORY LANDSCAPE: This provision implicates GDPR Article 28 sub-processing authorization obligations and Article 30 records of processing activities requirements, as the sub-processor chain is variable based on feature configuration rather than fixed at contract execution. Controllers must maintain accurate records of all processors and sub-processors, which requires tracking feature enablement across the Salesforce environment. Relevant enforcement authorities include EU supervisory authorities and equivalent bodies in jurisdictions where customers operate. (2) GOVERNANCE EXPOSURE: Medium to High for organizations with complex Salesforce environments where multiple Einstein, Agentforce, or AI-powered features are enabled across different business units. The dynamic nature of the sub-processor chain means that standard point-in-time sub-processor audits may not reflect the actual processing landscape if features are enabled or disabled between audit cycles. (3) JURISDICTION FLAGS: EU and EEA organizations face the most direct exposure given GDPR Article 28 requirements. Organizations in South Korea, Brazil, and other jurisdictions with sub-processor authorization obligations under national data protection law face similar considerations. Organizations in regulated sectors, particularly financial services and healthcare, should evaluate whether feature-triggered sub-processor activation aligns with sector-specific data processing restrictions. (4) CONTRACT AND VENDOR IMPLICATIONS: Procurement and legal teams should assess whether their DPA with Salesforce grants blanket authorization for the sub-processor chain disclosed in the full infrastructure table or requires specific authorization for each sub-processor, and whether that authorization mechanism accounts for feature-triggered additions. Vendor assessment processes should include a review of feature configuration states as a sub-processor inventory determinant. (5) COMPLIANCE CONSIDERATIONS: Compliance teams should implement a process for reviewing sub-processor implications before enabling new Einstein or Agentforce features, update records of processing activities to reflect feature-triggered sub-processor additions, and confirm that transfer impact assessments cover the sub-processors activated by the organization's current feature configuration.
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This provision creates a direct operational link between feature configuration decisions and sub-processor inventory: enabling Einstein NLP, generative AI, speech, or analytics features introduces additional sub-processors including AWS, Microsoft Azure, OpenAI, Deepgram, LiveKit, and Eleven Labs across multiple jurisdictions, requiring that organizations maintain a dynamic sub-processor map that reflects their current feature configuration.
Under this clause, the set of sub-processors processing Customer Data is not static but expands as additional features are enabled within covered services. The document states that if these features are enabled, Customer Data will be processed by the additional infrastructures, making feature activation decisions a direct determinant of the applicable sub-processor chain.
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