Secure AI Security Controls Best Practices
As GenAI moves beyond experimentation, leaders need confidence that the right security controls are in place—and that teams can apply them consistently across use cases, vendors, and business functions. This workshop clarifies control categories, minimum viable control baselines, how controls fit into day-to-day delivery and oversight, and what “effective” looks like when testing and reporting against standards.
Leave with a clear understanding of secure AI control best practices—and prioritized next steps to strengthen coverage, consistency, and audit readiness.
Security controls for GenAI are often discussed broadly, but applied unevenly—creating gaps and friction at scale.
- Control expectations are unclear: Leaders struggle to translate “secure AI” into specific control requirements teams can apply consistently.
- Baselines are inconsistent: Different groups define “good enough” differently, leading to uneven coverage and difficult approvals.
- Assurance is hard to prove: Without clear testing and reporting practices, it’s difficult to demonstrate effectiveness and compliance.
When controls aren’t defined, tested, and reportable, GenAI scale increases exposure.
We help leaders align on control best practices and the practical actions needed to operationalize them across GenAI initiatives.
- Control category clarity: Establish a shared language for what controls exist and what they’re intended to prevent or detect.
- Minimum viable control baselines: Define a practical baseline of controls that can scale across common GenAI use cases.
- Operationalization into delivery: Identify how control requirements become part of everyday workflows—not after-the-fact reviews.
- Effectiveness testing approach: Align on how to validate coverage and effectiveness so leaders can rely on control claims.
- Compliance reporting readiness: Define what leaders need to see to demonstrate adherence to AI control standards with confidence.
- Categorizing Technical Controls in GenAI
- Establishing Minimum Viable Control Frameworks
- Integrating Controls into Model and App Pipelines
- Testing Controls for Effectiveness and Coverage
- Reporting Compliance with AI Control Standards
Develop a shared understanding of secure AI security control best practices and how they apply across GenAI initiatives
Establish a prioritized list of next steps to strengthen control coverage and consistency across teams and vendors
Gain a practical view of what “minimum viable” controls look like for scalable oversight and approvals
Define a clear approach to validating control effectiveness and identifying meaningful gaps
Produce a reporting-ready outline of what to measure and present to demonstrate control compliance and accountability
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
4 hours
Intermediate
Shared collaboration space (virtual whiteboard or equivalent) and shared notes