GenAI & Risk

Valuable Outcomes:

• Learn from senior industry risk practitioners and academic thought leaders in the AI space what tools and practices strengthen your governance and risk infrastructure and help you leverage AI for maximum impact in your business.
• Build AI risk management skills through applying lessons learned from real-world case studies to situations of interest to you.
• Gain important insights on what AI transformation can do for your organization and how to execute an AI strategic transformation plan.
• Network with peers and build a community of practice around GenAI & Risk.

Networking Dinners: Join professionals in the DC metro area for dinner and begin building a network of peers who share their experience with real-world AI implementations.

Certification: Participants will receive a certificate of completion from the University of Maryland.

Designed for Executive Schedules

This program delivers enterprise-level insight in a focused, two-day format, allowing you to participate fully without stepping away from your responsibilities. Engage with faculty and peers while remaining accessible to your team and organization.

No travel. No disruption. High-impact learning.

Program Agenda

Day One (GenAI): Thursday, May 14, 8:30 a.m.-3:30 p.m.

How GenAI Is Creating Value
The program begins with an overview of generative AI and agentic systems and how organizations are unlocking measurable value from these technologies. Participants will explore core terminology, capabilities and limitations of generative AI, along with practical examples of how firms are deploying these tools across business functions. The session also highlights common use cases and lessons learned from early adopters to inform strategic decision-making.

What Successful Firms Do to Create Value
Building on the overview of generative AI capabilities, this session explores the organizational building blocks that enable firms to convert experimentation into sustained business value. Participants will explore the infrastructure, operating models and cultural shifts that distinguish leading firms from followers. Particular attention is given to redefining the roles of AI and humans to enable learning by doing and continuous improvement.

Sequencing Considerations for GenAI Initiatives
With value drivers and organizational enablers established, this session introduces a structured framework for sequencing generative AI initiatives across the enterprise. Participants will assess how to dimension the AI investment landscape, estimate incremental value and level of effort, and prioritize use cases strategically. The session also explores organizational design considerations, including centralization vs. decentralization, and how to rewire the organization to support AI-enabled transformation.

Effective AI Governance and Risk Management
Complementing the discussion of prioritization and implementation, this session addresses the governance and risk considerations that must be embedded into AI strategy from the outset. Participants will explore how AI amplifies traditional risks, how those risks can be mitigated, and how organizations determine when to proceed with AI initiatives. The session integrates governance frameworks with case-based discussion to equip leaders with practical tools for oversight and decision-making.

Facilitated Reflections: Value Creation and Prioritization
Concluding Day One, this facilitated session integrates insights from value creation, sequencing and governance discussions into practical application within participants’ own organizations. Through structured small-group discussions, participants will examine how generative AI value creation, sequencing and governance considerations influence their scope, prioritization decisions and strategic navigation of internal governance structures. Key themes and insights will be summarized and shared with the full group.

Day Two (Risk): Friday, May 15, 8:30 a.m.-3:30 p.m.

Case Studies of GenAI Risk
Day Two begins by grounding the discussion in real-world case studies that illustrate how generative AI and agentic system risks emerge and impact organizations. Participants will analyze real-world examples to understand how risks emerge, propagate and impact organizations. The discussion emphasizes identifying common risk themes and patterns to strengthen proactive risk identification and mitigation strategies.

What Are Institutions and Regulators Doing About AI?
Building on the risk themes identified in the case studies, this session examines how institutions and regulators are responding to the rapid adoption of AI technologies. Participants will explore the evolving competitive landscape, regulatory expectations and supervisory approaches related to AI governance and model risk management. The session contrasts traditional model risk frameworks with AI-specific challenges to clarify emerging compliance and oversight expectations.

Does Modernized Risk Management Include AI Use Cases?
Extending the regulatory discussion, this forward-looking session considers how enterprise risk management frameworks must evolve to address AI-enabled business models. Participants will explore technological and organizational trends, assess urgency and readiness, and identify implications for boards and executive leadership. The session also examines how risk management functions can strategically sponsor and support AI use cases while modernizing governance frameworks.

Framework and Best Practices for Managing Risk in Generative AI
Drawing together regulatory insights and modernization themes, this session presents a practical framework for managing risk in generative AI transformation efforts. Participants will examine how roles across risk, IT and operational functions are being disrupted and reengineered, and how existing AI risk management frameworks can inform internal design. The session integrates strategy setting, governance structures and policy development into a cohesive approach.

Facilitated Reflections: Managing GenAI Risk
In the final session, participants reflect on workshop insights and consider how they will operationalize learnings within their organizations. Through structured breakout discussions, participants will explore how the workshop influences their near-term actions and long-term strategy for AI risk management. Key themes and commitments will be synthesized and shared with the broader group.

Certificate Sample