What Is
Enterprise AI Security?
Enterprise AI security is a corporate security framework that controls the risks of data leakage, Shadow AI, and compliance violations arising from employee use of generative AI services like ChatGPT, Claude, and Gemini.
4 AI Security Threats Facing Enterprises
As generative AI service adoption grows, new threats have emerged that existing security frameworks cannot address.
Customer data, source code, and internal documents are entered directly into ChatGPT and Claude prompts.
Employees use AI services not approved by IT for work tasks.
Contracts, financial statements, and design documents are uploaded to AI services.
Risk of violating data regulations such as GDPR and privacy laws increases.
4 Steps to Build Enterprise AI Security
A field-validated step-by-step approach to building AI security.
Assess AI Usage
Identify which AI services are being used, how often, and by which departments.
- Check enterprise AI usage dashboard
- Detect Shadow AI services
- Analyze usage by department and role
Define Sensitive Data Policy
Clearly define what information may and may not be entered into AI services.
- Define PII categories
- Source code and internal document classification
- Design tiered policies by department
Deploy Endpoint Solution
Deploy endpoint agents enterprise-wide by directly installing on Windows and macOS devices.
- Direct install on Windows · macOS
- Install without network changes
- Run in detection-only mode for 2 weeks
Activate Policies and Monitor
Analyze detection results and activate blocking policies incrementally.
- Review detection reports
- Prioritize high-risk events
- Quarterly policy review and update