AI Security Controls Every Business Should Consider

Businesses implementing AI should evaluate security controls across data access, processing, storage, integrations, and monitoring. A comprehensive approach to AI data security for businesses can include RBAC, MFA, encryption, data masking, secure API endpoints, audit logs, vendor assessments, and human approval mechanisms. Data classification helps determine which controls are required for different information types. Organisations should also monitor AI workflows for unusual behaviour and review security configurations regularly. These measures can help create a more controlled environment for AI adoption. Security should be incorporated into architecture from the beginning rather than added only after an AI application reaches production.