Managing
AI Use Cases

AI Governance — Module 2 of 4

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Learning objectives

“As an AI governance professional, I want to learn how to register AI use cases, conduct impact assessments, and manage lifecycle stages in ​ValidMind.”

This second module is part of a four-part series:

AI Governance

Module 2 — Contents

1. Use case inventories
2. Risk classification
3. Impact assessments
4. Lifecycle stages

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Use case inventories

What is a use case inventory?

A centralized registry of all AI systems and their purposes, use case inventories help you:

  Understand where AI is used

  Track ownership and accountability

  Assess aggregate risk exposure

  Demonstrate governance to regulators

Inventory fields

Configure custom inventory fields for AI governance:

Field type	Examples
Classification	Risk tier, impact level
Ownership	Use case owner, business sponsor
Purpose	Intended use, use boundaries
Status	Lifecycle stage, approval status

Custom field configuration

The inventory in action

The ValidMind inventory

The Inventory displays AI use cases with:

• Tier — Risk classification level
• Model owner — Accountability assignment
• Model stage — Current lifecycle stage

Risk classification

Why classify risk?

Risk classification enables proportionate governance. Higher-risk AI systems receive:

  More rigorous review

  Additional documentation requirements

  Enhanced monitoring

  Stricter approval gates

Classification schemes

Align your classification to relevant regulations:

Framework	Classification levels
EU AI Act	Prohibited, high-risk, limited-risk, minimal-risk
Internal	Critical, high, medium, low
Tiered	Tier 1, Tier 2, Tier 3, Tier 4

Configuring risk tiers

In ​ValidMind, you can:

1. Add custom fields for risk classification
2. Configure different workflows per tier
3. Apply documentation templates by tier
4. Generate reports filtered by risk level

Risk overview

Impact assessments

Purpose of impact assessments

Impact assessments evaluate potential risks and harms from AI deployment. They document:

  Who is affected by the AI system

  What decisions the AI influences

  Potential for harm or discrimination

  Mitigating controls

Impact assessment process

1. Identify stakeholders — Who does this AI system affect?
2. Assess impact — What are the potential consequences?
3. Evaluate risks — What could go wrong?
4. Document controls — How are risks mitigated?
5. Review and approve — Governance sign-off

Recording assessments

Use ​ValidMind to:

  Attach impact assessment documentation

  Track assessment completion status

  Route assessments through approval workflows

  Maintain audit trail of governance decisions

Lifecycle stages

AI governance lifecycle

The AI governance lifecycle moves from intake and risk assessment through documentation and validation to a formal approval gate, then deployment, ongoing monitoring, and periodic review — with a feedback loop so systems can be re-assessed and re-approved when needed.

Managing stage transitions

​ValidMind tracks AI systems through their lifecycle:

• Status fields indicate current stage
• Workflows control transitions
• Documentation captures stage requirements
• Audit trail records all changes

Next steps

Continue to Module 3 to learn about configuring AI workflows.

Module 3: Configuring AI workflows