# Ai Governance Architect

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- **Type:** Skill
- **Install:** `agentstack add skill-prvthmpcypher-skills-business-ai-governance-architect`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [prvthmpcypher](https://agentstack.voostack.com/s/prvthmpcypher)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [prvthmpcypher](https://github.com/prvthmpcypher)
- **Source:** https://github.com/prvthmpcypher/skills-business/tree/main/skills/ai-governance-architect

## Install

```sh
agentstack add skill-prvthmpcypher-skills-business-ai-governance-architect
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# AI Governance Architect

Establishes enterprise AI governance frameworks balancing innovation velocity with risk management, compliance, and responsible AI principles.

## Phased Workflow

### Phase 1: AI Risk Assessment & Inventory
1. Catalog all AI/ML models in production with metadata: owner, training data provenance, use case, risk tier.
2. Classify models by risk level: Low (internal productivity), Medium (customer-facing recommendations), High (financial/healthcare/legal decisions).
3. Assess each model for: bias risk, explainability requirements, data privacy exposure, and regulatory compliance.

### Phase 2: Policy & Framework Design
1. Define responsible AI principles: Fairness, Transparency, Accountability, Privacy, Safety, Human Oversight.
2. Establish model lifecycle governance: development standards, pre-deployment review, monitoring, retirement.
3. Design human-in-the-loop (HITL) protocols for high-risk decisions with clear escalation paths.

### Phase 3: Auditing & Continuous Monitoring
1. Implement bias auditing: statistical parity, equalized odds, disparate impact analysis across protected classes.
2. Build model performance monitoring dashboards with drift detection and fairness metric tracking.
3. Establish incident response procedures for AI system failures or harmful outputs.

## Verification & Quality Checklist
- [ ] AI inventory complete with risk classifications for all production models.
- [ ] Responsible AI policy documented and approved by leadership.
- [ ] Bias auditing procedures defined with quantitative fairness thresholds.
- [ ] HITL escalation paths tested and documented for all high-risk use cases.

## Anti-Patterns & Constraints
- NEVER deploy high-risk AI models without documented human oversight mechanisms.
- NEVER treat AI governance as a one-time checklist; implement continuous monitoring.
- NEVER ignore demographic subgroup analysis when evaluating model fairness.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [prvthmpcypher](https://github.com/prvthmpcypher)
- **Source:** [prvthmpcypher/skills-business](https://github.com/prvthmpcypher/skills-business)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-prvthmpcypher-skills-business-ai-governance-architect
- Seller: https://agentstack.voostack.com/s/prvthmpcypher
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.