AI governance assessment
A practical AI governance assessment guide for SMEs
AI governance is not just for enterprise legal teams. Small businesses that adopt AI without clear accountability, policy and oversight expose themselves to compliance failures, bad decisions and customer distrust. This guide gives you a lightweight framework to assess and improve AI governance in a few hours.
Risk ownership
Name a single accountable owner for AI decisions, model selection and incident response. Ambiguity is where liability hides.
Policy and documentation
Document what AI tools are approved, what data they may access, and how outputs are reviewed before they affect customers or staff.
Human oversight
Define which decisions require human sign-off, who can override AI outputs, and how staff report mistakes or bias.
Compliance and data protection
Map AI use to GDPR, sector regulators and customer contracts. Check data retention, sub-processors and cross-border transfers.
Incident response
Plan for hallucinations, data leaks and model downtime. Test the plan like any other business continuity exercise.
AI governance assessment checklist
Score each item as Not started, Partial or In place. Any item below In place is a gap to close before scaling AI use.
- We have a named AI governance lead.
- We maintain a register of AI tools in use and their data sources.
- We have an AI acceptable-use policy staff have read.
- We review AI outputs for accuracy before acting on them.
- We know which AI decisions require human approval.
- We have assessed GDPR / data-protection impact for each tool.
- We understand our AI providers' sub-processors and retention terms.
- We have an incident response plan for AI failures.
- We train staff on AI limitations, bias and safe prompting.
- We review this governance framework at least quarterly.
Turn this checklist into a scored assessment
Readiness scores your AI governance alongside strategy, data, technology, skills and processes — then builds a prioritised roadmap for your business.