Slack may use information about how you use the service, potentially including content and usage data, to train its AI and machine learning models as part of product improvement.
This analysis describes what Slack'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 policy's authorization to use data for AI model training is relevant for users and enterprise customers who want to understand whether their interaction data or content contributes to AI development, which is an increasingly material privacy consideration.
Interpretive note: The policy does not clearly specify whether Customer Data (messages, files) is included in or excluded from AI training use; this ambiguity means the practical scope of this provision depends on Slack's separate AI product terms and DPA language.
Usage data and potentially interaction data may be used to train Slack's AI and machine learning models, a practice that is disclosed in general terms but may not be fully transparent to individual users about the specific data types involved.
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"We use information we collect to provide, maintain, improve, and develop our products and services. We also use information to develop new products and features. For example, understanding how our customers use our services allows us to improve our services and may be used to train our AI and machine learning models.— Excerpt from Slack's Slack Privacy Policy
REGULATORY LANDSCAPE: This provision engages GDPR's requirement for a lawful basis for processing (Article 6) and, where AI training involves special categories of data inadvertently captured in messages, Article 9. The EU AI Act (effective 2024-2026 phased implementation) may impose additional transparency and documentation requirements on AI systems trained on user data. The FTC has issued guidance on AI and data practices, including requirements that data use for AI training be consistent with the context in which data was collected. The UK ICO has published guidance on AI and data protection. GOVERNANCE EXPOSURE: Medium. The provision authorizes AI training use in general terms without specifying whether Customer Data (employee messages and files) is included or excluded. This ambiguity is material for enterprise customers who may not consent to their proprietary communications being used for model training. Slack's AI-specific terms or DPA addenda may contain more specific restrictions, and compliance teams should review those documents. JURISDICTION FLAGS: EU/EEA users have heightened exposure given GDPR's requirement for a specific lawful basis for AI training use, which may not be adequately established by a general 'legitimate interest' or 'contract performance' basis depending on the data involved. California users may have CCPA-based rights to opt out of certain uses of their data for AI development if characterized as 'sharing' for commercial purposes. CONTRACT AND VENDOR IMPLICATIONS: Enterprise customers should review Slack's AI product terms and any DPA addenda to confirm whether Customer Data is excluded from AI model training, and should include explicit contractual restrictions if needed. Procurement due diligence should assess whether Slack AI features require separate consent or disclosure to employees under applicable labor and privacy law. COMPLIANCE CONSIDERATIONS: Organizations deploying Slack AI features should update their employee privacy notices to disclose AI-assisted processing and any associated data uses. Data minimization assessments should evaluate whether sensitive content transmitted via Slack is adequately protected from inclusion in AI training pipelines. Compliance teams should request Slack's current AI data use documentation and verify alignment with their own AI governance policies.
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The policy's authorization to use data for AI model training is relevant for users and enterprise customers who want to understand whether their interaction data or content contributes to AI development, which is an increasingly material privacy consideration.
Usage data and potentially interaction data may be used to train Slack's AI and machine learning models, a practice that is disclosed in general terms but may not be fully transparent to individual users about the specific data types involved.
ConductAtlas has identified this type of provision across 2 platforms. See the full comparison.
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