AI governance
AI governance for scaling with accountability, boundaries and evidence.
We define who owns each system, which uses are permitted, which information may be used, how performance is evaluated and what happens when an error or risk appears.
Control and accountability
Governing AI means being able to explain who decides, with which information and within which limits.
A practical framework combines policies, owners, a system inventory, evaluation, records, human oversight, escalation and stop mechanisms.
- Owners and responsibilities
- Permissions, data and authorised uses
- Evaluation, records and incidents
01 / Responsibility
Governance is not about slowing down. It is about knowing who decides and what happens when something fails.
Organisations need usage criteria, named owners, records, evaluation and escalation processes.
FAQ
Frequently asked questions
Is AI governance only needed in large companies?
No. Any organisation using AI in relevant processes needs responsibilities, permissions and review criteria proportionate to risk.
Does governance slow innovation?
No. A clear framework speeds implementation by reducing ambiguity and defining the conditions each case must meet.
Content reviewed: 29 July 2026