Secure AI Risk Management Best Practices
As GenAI scales, leaders need a clear way to identify the most material risks, apply the right controls, and keep risk profiles current as usage changes. This workshop builds shared understanding of secure AI risk management best practices—so oversight becomes consistent, decisions are faster, and accountability is easier to sustain across initiatives.
Leave with a clear view of your highest-priority GenAI risks—and actionable next steps to strengthen how they’re assessed, controlled, and monitored.
GenAI introduces new risk patterns that many organizations don’t manage consistently across teams, vendors, and use cases.
- Risk is hard to see end-to-end: Leaders often lack a shared view of where risk can arise across people, data, vendors, and operational workflows.
- Not all risks deserve equal attention: Without a clear prioritization approach, teams over-control low-value concerns and under-control material exposure.
- Controls and monitoring lag adoption: Policies exist, but they don’t consistently translate into practical controls and ongoing risk monitoring.
When risk management isn’t repeatable, GenAI scale creates avoidable exposure—and slows execution through uncertainty and rework.
We equip leaders with best practices and a practical approach to manage GenAI risk with clarity and continuity.
- End-to-end risk mapping: Build a shared view of where GenAI risks can emerge across the full risk surface—not just one team’s lens.
- Materiality-based prioritization: Establish a simple way to focus on the risks that are most likely and most impactful.
- Control selection guidance: Align on control types that fit the risk and the business context—without overburdening teams.
- Repeatable assessment process: Define a practical risk assessment workflow that supports consistent reviews and decision-making.
- Ongoing risk monitoring: Set expectations for how risk profiles are tracked, updated, and improved as GenAI usage evolves.
- Mapping Risks Across the AI Stack
- Prioritizing High-Impact and Likely Risks
- Defining Controls to Mitigate AI Risks
- Developing Risk Assessment Processes
- Monitoring and Updating Risk Profiles Continuously
Develop a shared understanding of secure AI risk management best practices leaders can apply consistently
Establish a prioritized view of the most relevant GenAI risks to address first
Define a practical next-step plan for improving risk assessment, control selection, and oversight
Create a clear outline of how controls should map to risk levels and business context
Adopt a lightweight approach for keeping GenAI risk profiles current as initiatives scale
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
4 hours
Beginner to Intermediate
Shared collaboration space (virtual whiteboard or equivalent) and shared notes