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risk-management

Identify and manage AI-related risks across lifecycle and governance.

2|Updated Feb 4, 2026
Search Tags:#compliance#governance#risk-assessment#risk-management#incident-response#erm#ai-risk
One-click install
npx skills add https://github.com/lexbeam-software/eu-ai-governance-plugin --skill risk-management-lexbeam-software
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: risk-management
Source: https://github.com/lexbeam-software/eu-ai-governance-plugin/tree/main/skills/risk-management
Command: npx skills add https://github.com/lexbeam-software/eu-ai-governance-plugin --skill risk-management-lexbeam-software

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI risk management across the lifecycle requires a structured taxonomy, assessment method, controls, monitoring KPIs, and incident response aligned to enterprise risk frameworks.

Core Features & Use Cases

  • AI risk taxonomy and categorization
  • Risk assessment methodology, scoring, and DPIA triggers
  • Monitoring KPIs and incident response playbooks

Quick Start

Describe your AI risk landscape and trigger an end-to-end risk assessment using the risk-management taxonomy.

Frequently Asked Questions about risk-management

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is AI risk assessment and how does it align with enterprise risk frameworks?▼

AI risk assessment identifies and manages AI-related risks across the lifecycle using a structured taxonomy and scoring methodology aligned to ISO 31000, COSO, and AI Act principles.

How do I conduct an end-to-end AI risk assessment for enterprise deployments?▼

You conduct an AI risk assessment by describing your AI risk landscape to trigger a structured evaluation using a defined risk taxonomy, scoring methodology, and governance controls.

When do I need a Data Protection Impact Assessment trigger for AI systems?▼

A DPIA trigger is needed during AI risk assessment when evaluating risk categories and scoring methodology to identify high-risk deployments requiring compliance governance and incident response playbooks.

Does this AI risk management approach support ISO 31000 and COSO frameworks?▼

Yes, this AI risk management approach supports ISO 31000 and COSO frameworks by defining risk categories, controls, KPIs, and incident playbooks aligned with these enterprise risk governance standards.

What's the best way to define incident response playbooks for AI governance?▼

The best way to define incident response playbooks for AI governance is using a structured risk management taxonomy that categorizes AI risks and aligns monitoring KPIs with operational compliance controls.

Can I use this risk-management taxonomy for enterprise AI audits?▼

Yes, you can use this risk-management taxonomy for enterprise AI audits because it applies to enterprise AI deployments and provides structured risk categorization, scoring, and KPIs for compliance verification.

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