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This recorded session includes the session video, handouts, presentation and links to the Monday Roundtables. This Package is valid for 30 days.
This session was recorded on July 9, 2026
Get Free AccessFederal agencies are under increasing pressure to deploy Artificial Intelligence (AI) capabilities while maintaining security, transparency, compliance, and public trust. As agencies accelerate AI adoption, leaders must establish practical approaches to identify, assess, prioritize, and mitigate AI-related risks across the entire AI lifecycle.
Pursuant to Executive Order (EO) 14179 Removing Barriers to American Leadership in Artificial Intelligence, and OMB Memo M-25-21, federal agencies are required to accelerate adoption of AI. At the same time, EO 14409 Promoting Advanced AI Innovation and Security lays out the importance of mechanisms such as The NIST AI Risk Management Framework (AI RMF) that aims to establish frameworks, risk management practices, and mechanisms that ensure AI systems are secure, transparent, accountable, and aligned with mission objectives.
This 60-minute briefing helps agency AI stakeholders close that gap. Participants will leave with a clear, defensible way to find, score, and rank AI risk across a model's full life, from data and training to use and monitoring. The method maps to the NIST AI RMF and the M-25-21 rules for high-impact AI and we will turn the M-25-22 procurement rules into plain contract terms. This will help your AI team build risk controls into contracts before award, not after. Presenters will provide insight on live threats and use real agency cases. Trust and speed are not a trade-off. This session will show you how to keep both.
What You'll Learn:
Attendees will learn how to:
Why Attend
Federal agencies are increasingly expected to accelerate AI adoption while maintaining compliance, security, and mission effectiveness. This briefing provides practical guidance for balancing innovation with responsible risk management and offers actionable strategies that can be immediately applied within federal programs and acquisitions.
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Topical Overview: Assessing AI Risk
How AI Risk Differs from Traditional Risk
The Impact of AI Risks
Trends in AI Risk
The Impact of AI Risks
Agentic AI: The New Risk Frontier
AI Risk Across the System Lifecycle
Risk Assessment Methodologies
Best Practices to Reduce AI Threats
Building AI Risk Into Procurement
When AI Fails: Incident Response & Recovery
Next Steps and Final Remarks
Q&A