AI Policy for IT Managers
IT Managers are the hands-on implementers of AI governance policy. They must translate high-level directives into technical controls covering network monitoring, access management, and data-loss prevention. Without proper IT-level enforcement, even the best AI policies remain paper exercises.
Primary Responsibilities
- Implementing technical controls to monitor and restrict unauthorized AI tool usage on the network
- Managing access permissions and authentication for approved AI platforms and APIs
- Maintaining an up-to-date inventory of all AI tools, plugins, and browser extensions in use
- Configuring data-loss-prevention rules that prevent sensitive data from reaching external AI services
- Supporting AI model deployment pipelines with proper version control and rollback procedures
- Responding to IT tickets related to AI tool access, performance, and integration issues
Questions Auditors Will Ask
- What technical controls prevent employees from using unapproved AI tools on the corporate network?
- How is the AI tool inventory maintained, and how often is it reviewed?
- Can you demonstrate that DLP rules cover data sent to external AI APIs?
- What rollback procedures exist for AI model deployments that produce unexpected results?
How PolicyGuard Helps
- Automated AI tool discovery that scans network traffic and endpoint activity for shadow AI
- Integration-ready API that connects PolicyGuard to your existing ITSM and SIEM platforms
- Policy enforcement engine that automatically blocks unapproved AI tools based on your allow-list
PolicyGuard provides IT Managers with automated tool discovery, DLP integration, and a policy enforcement engine that works with your existing stack. Turn AI policies into working controls.
