AI Governance, Responsible AI, Risk & Compliance
Proportionate AI governance: match controls to consequence
Treating every AI use case as equally risky creates bureaucracy without creating equal safety.
Look at consequence
What can happen if the system is wrong? Drafting internal copy and denying access to a service belong in different control tiers.
Look at autonomy
A system that recommends an action is different from one that can execute it using credentials, money or external communication channels.
Look at reach
An error affecting one internal user is different from a system making thousands of decisions per hour.
Scale the controls
Use stronger testing, monitoring, approval and escalation where consequence is material. Keep low-risk experimentation light enough that teams can still learn.
Continue the system
Keep exploring
Put it to work
Turn the idea into an operating move.
Continue with a practical resource, a structured system, or an advisory conversation when context matters.
