AI can support marketing, customer service, internal documentation and analysis. It can also expose confidential information, produce inaccurate claims or create decisions no one can explain. Trust depends on managing those risks as part of the workflow.
Know what data is going in
Before using a tool, identify the information staff may enter, whether personal or confidential data is involved, where it is processed and retained, and whether it may be used to improve a model. Check the supplier terms and the organisation’s data protection obligations.
Where a proposed use is likely to create a high risk to individuals, obtain appropriate data protection advice and assess whether a formal impact assessment is required.
Choose tools for the risk
- Review data handling, retention and model-training controls.
- Use appropriate access controls and keep accounts under organisational ownership.
- Understand where data is processed and how it is protected.
- Prefer tools that provide the governance needed for the intended use.
The same standards applied to other suppliers, customer data and published claims should apply when AI is involved.
Keep people responsible
AI output should be reviewed before it affects a customer, employee or commercial decision. The level of review should reflect the consequence of an error. Sensitive complaints, employment decisions, legal claims and safety information need particular care.
Document the working method
A lightweight AI policy can record approved tools, prohibited information, expected checks, ownership and escalation. Pair it with real examples and training so staff can apply it when the work is busy.
This article is general business guidance, not legal advice. The right controls depend on the data, tool, purpose and risk of the specific use.