Building an AI security program
A practical guide to building an enterprise AI security program from zero. From organizational structure through technical controls to maturity assessment — every step for security teams starting their AI security journey.
Phase 1: Foundation (Weeks 1-4)
- Appoint AI security lead and establish cross-functional stakeholders
- Deploy shadow AI detection for baseline visibility
- Deploy PII masking for immediate data protection
- Enable audit trails for compliance readiness
Phase 2: Governance (Months 2-3)
- Develop AI governance framework with policies and acceptable use
- Implement automated policy enforcement
- Deploy prompt firewall for injection detection
- Begin compliance evidence generation
Phase 3: Integration (Months 3-6)
- Connect AI security to SOC operations
- Deploy document leak detection for IP protection
- Conduct LLM threat modeling for risk assessment
- Integrate with existing GRC and incident response programs
Phase 4: Maturity (Ongoing)
- Regular red teaming exercises to validate controls
- Continuous monitoring and policy refinement based on detection metrics
- Board-level reporting on AI risk posture and compliance
- Adapt to evolving regulatory requirements
Start building today
Deploy foundational AI security controls in the first week.
Frequently asked questions
Where should AI security sit in the organization?+
Under the CISO, with a dedicated AI security lead who coordinates across security, engineering, legal, and compliance teams. The AI security program should integrate with existing GRC, SOC, and incident response programs — not operate as a separate silo.
What is the minimum viable AI security program?+
Minimum viable: (1) Prompt inspection with PII masking, (2) audit trail for compliance, (3) shadow AI detection for visibility. These three controls can be deployed in weeks and address the highest-priority risks. Additional capabilities (governance, SOC integration, document protection) can be added incrementally.
How do I measure AI security program maturity?+
Key maturity indicators: percentage of AI interactions under governance, detection coverage (PII, injection, document similarity), policy enforcement consistency, audit trail completeness, SOC integration status, and compliance audit readiness.