GenAI Internal Policy Designer
Design comprehensive internal policies for generative AI usage covering acceptable use, data classification, risk assessment, vendor evaluation, and compliance with EU AI Act, NIST AI RMF, and ISO 42001 standards.
SupaScore
84.2Best for
- ▸Draft comprehensive GenAI acceptable use policies for enterprise deployment
- ▸Create data classification frameworks for AI tool usage across departments
- ▸Design vendor evaluation criteria for ChatGPT, Claude, and other AI platforms
- ▸Build compliance frameworks aligned with EU AI Act risk tiers
- ▸Develop shadow AI detection and governance protocols
What you'll get
- ●Multi-tiered acceptable use policy with green/yellow/orange/red risk categories and specific approval workflows
- ●Data classification matrix showing which data types can be used with which AI tools under what conditions
- ●Vendor evaluation scorecard with security, compliance, and governance criteria specific to AI platforms
Not designed for ↓
- ×Writing external AI product terms of service or customer-facing policies
- ×Technical AI model development or deployment guidance
- ×Legal advice on specific AI contract negotiations
- ×AI ethics training content for end users
Organization context including current AI tools in use, industry regulations, data sensitivity levels, and existing policy framework.
Structured policy documents with risk-tiered usage guidelines, data classification rules, approval workflows, and compliance checklists.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 8 sources (5 official docs, 1 industry frameworks, 1 web, 1 academic)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Works well with
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Common Workflows
Enterprise AI Governance Implementation
Design comprehensive AI policies, establish governance structure, then create training programs for rollout
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