An AI governance checklist for mid-sized companies
Governance does not require a committee. It requires written answers to a short list of uncomfortable questions.
By Xonique Editorial TeamEditorial Desk
Published · 6 min read
Governance frameworks written for large regulated institutions rarely transfer to a company of two hundred people. What does transfer is the underlying discipline: knowing what is deployed, who approved it and how it is retired.
Keep a register
A single list of every AI-assisted workflow in use, its owner, the data it touches and its review status covers most of what an early governance conversation requires.
Define one review route
One route, one form, one small group of reviewers. Multiple parallel processes create the appearance of oversight without the substance.
What to check before you commit
- Maintain a register of deployed AI workflows.
- Route every new use case through one review path.
- Document what the system must never be used for.
- Set a review date on each entry.
A note on measurement
Teams that treat AI governance as an engineering project usually measure the wrong thing. Instrument the business outcome first — cycle time, cost per transaction, resolution rate, revenue retention — then work backwards to the technical metrics that move it.
- governance
- risk
- policy
