AI adoption and governance
AI governance for growing businesses: the minimum useful system
Good governance makes safe progress easier and keeps control proportionate.
Define safe experimentation
Give teams a clear zone in which they can test approved tools using non-sensitive information. State what cannot be entered, which outputs require human checking and where questions should go.
Increase control with consequence
Use simple risk tiers based on data sensitivity, autonomy, affected people, reversibility and commercial consequence. An internal drafting assistant needs a lighter route than an automated customer decision.
Govern the whole portfolio
Review owners, evidence, incidents, costs and adoption across the active use cases. Tool approval alone does not show whether AI is creating value or quietly becoming unmanaged infrastructure.
Put the answer to work
Use this guidance against one live decision. Name the outcome, owner, evidence and next review point, then record what the business will do differently. Where the choice carries material legal, technical, financial, security or people consequences, bring the relevant specialist into the decision while keeping business ownership explicit.
What to carry into the work
- Create a safe experimentation zone
- Use consequence-based risk tiers
- Name an owner for every live use case
- Review value, adoption and risk together