AI governance

Stage 2 of 8 · 6 lessons · ~3 weeks

AI inventory: know what you run

You cannot govern what you cannot see. Design an AI register, run discovery for shadow AI, classify each system, assign a risk tier and a named owner, and set review cycles that teams will actually follow.

Start: What counts as an AI system

Lessons· one lesson for each topic, in this order

  1. 1What counts as an AI system
  2. 2Finding shadow AI
  3. 3Classifying systems and assigning a risk tier
  4. 4Ownership: every system has a named person
  5. 5Model registries and the inventory
  6. 6Running the inventory as a governance register

Do this

  • Invent a realistic sample company, such as a fintech, a hospital chain or an online retailer, with its teams.
  • List the AI it would plausibly use: built, bought and used by staff on their own.
  • Write three survey questions to find shadow AI that people would answer honestly.
  • Describe each system with purpose, users, affected people, data and vendor.
  • Assign an EU AI Act role and tier and an internal tier, with one line of reasoning each.
  • Name an accountable owner and a technical owner for each system.
  • Mark which systems need a model registry entry and what it would record.

Start with· follow one of these

Practise

  • Build the register as a database with an intake form and review dates

  • Draw how one high-risk system takes data, makes decisions and reaches people

Keep handy

Also worth your time

Before moving on: An AI inventory for a sample company of about 50 staff: at least eight systems including two shadow AI uses and two vendor features, each with purpose, owner, data, EU AI Act role and tier, internal tier and a written reason, plus a short note on how you found them.

Tauseef's advice
Make the intake form short enough that a busy manager fills it in. You can always ask follow-up questions for high-risk systems; you cannot govern systems nobody declared.

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