This workshop offers a deep dive into secure AI insights—how to consolidate meaningful security signals, interpret them to spot gaps early, and convert findings into prioritized actions. Participants align on what to measure, how to track progress over time, and how to communicate security health in a way that supports governance decisions and responsible scale.
Leave with a clear set of secure AI insight best practices—and actionable next steps to improve visibility, prioritization, and follow-through.
As GenAI adoption grows, many organizations struggle to translate security signals into clear, decision-ready insight.
- Signals without clarity: Teams collect data, but leaders don’t get a usable picture: making it hard to know what’s working and what needs attention.
- Gaps surface late: Vulnerabilities and control weaknesses aren’t identified early enough: leading to escalations and reactive rework.
- No closed-loop accountability: Issues get logged, but resolution isn’t tracked consistently over time: so the same problems recur.
Without insight-driven security oversight, GenAI scale becomes harder to trust and harder to govern.
We align stakeholders on secure AI insight best practices that make security measurable, actionable, and easier to sustain.
- Security insight model: Define what leaders should see to understand security health across GenAI initiatives in a consistent way.
- Signal-to-gap translation: Establish a practical approach for turning security signals into clearly articulated vulnerabilities and system gaps.
- Prioritization and action planning: Convert findings into a ranked set of actions and control improvements tied to risk and business impact.
- Issue tracking and follow-through: Set expectations for tracking remediation progress and verifying closure over time.
- Governance-ready communication: Create a clear reporting approach that supports oversight forums, escalation decisions, and stakeholder alignment.
- Aggregate security metrics and telemetry from AI systems
- Identify vulnerabilities and system gaps from security signals
- Translate findings into prioritized security actions and controls
- Track resolution of security issues over time
- Communicate security health across governance stakeholders
- Define a shortlist of the most meaningful secure AI security signals and metrics to track consistently
- Adopt a practical approach for translating signals into identified gaps and vulnerabilities
- Establish a prioritized set of next-step security actions and control improvements to pursue
- Apply a lightweight method for tracking issue resolution and verifying closure over time
- Create a governance-ready communication outline for sharing security health with key stakeholders
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
2 hours
Beginner to Intermediate
Shared collaboration space (virtual whiteboard or equivalent) and shared notes