tech-data-deployment

Use when matching enterprise data sensitivity to AI deployment pattern, deciding whether a use case can run on consumer ChatGPT vs enterprise SaaS vs VPC vs air-gapped, suppressing shadow AI, or specifying the control stack required per data class. Phrases like "can we use ChatGPT for this?", "is this data safe for an enterprise SaaS LLM?", "what controls do we need for PII/PHI in this AI workflow?", "shadow-AI is everywhere, how do we sanction tools?", "what deployment pattern fits regulated data?" all trigger this skill. Maps each data sensitivity class to one of five deployment tiers, names the minimum control stack per tier under NIST AI RMF / ISO 42001 / EU AI Act, and outputs a deployment-pattern verdict (Approved / Conditional / Blocked) with a control checklist and regulatory citations.

适合你，如果你需要判断哪些AI工具可用于敏感数据，并满足监管要求。