AI adoption and governance
AI governance for growing businesses: the minimum useful system
Governance should make safe progress easier, not put a committee around every experiment.
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
An internal drafting assistant and an automated customer decision should not pass through the same process. Use simple risk tiers based on data sensitivity, autonomy, affected people, reversibility and commercial consequence.
Govern the portfolio, not only the tools
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.
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