“Governance” sounds like committees, forms and waiting. No wonder teams prefer to use AI around the rules. Yet the opposite is possible: governance that speeds things up because it removes uncertainty.
1. Permitted first
Most policies start with prohibitions. Better: start with a clear list of what is allowed without asking. Approved tools, approved data classes, approved use cases. Everything else goes through a short, defined process.
2. One page, not forty
If a policy doesn’t fit on one page, nobody reads it. Details belong in appendices for specialists. Everyone else needs five to ten clear rules in plain language.
3. Technology before paper
A rule enforced technically doesn’t need to be memorised. Data classification that automatically blocks confidential documents. Approved models provided centrally. Logging that runs in the background. Paper is the exception, not the default.
4. Accountability with a name
Every AI system needs an accountable person - not a committee. They decide on changes, watch quality and risk, and are reachable when something goes wrong.
The test
Good AI governance passes a simple test: does a new employee know after five minutes what she may do with AI, what not - and whom to ask? If yes, the governance is good. If not, it merely exists.
