AI Security
The practical foundations of secure AI adoption
A clear starting point for protecting data, managing access and establishing responsible oversight.
Start with the outcome, not the tool
Secure AI adoption starts with a defined business need. A useful outcome gives teams something concrete to assess, govern and improve.
Choose a contained use case where the information involved is understood and a person can review the result before it affects a customer or business decision.
Know what data is entering the system
Before a team uses an AI service, establish which information is permitted, which is restricted and which must never be entered. The same rules should apply to documents, copied text and connected data sources.
- Classify the information involved.
- Confirm how the provider stores and uses submitted data.
- Limit access to the people who need it.
- Keep sensitive personal and confidential information out of unapproved tools.
Keep meaningful human oversight
AI can accelerate analysis and drafting, but accountability remains with the organisation. Define who checks outputs, what they check and when an issue must be escalated.
A lightweight review process is often enough for an early use case. The important thing is that it is explicit, repeatable and proportionate to the risk.