GenAI & Risk

Executive Certificate Program

Generative AI adoption is accelerating faster than most governance and risk frameworks can adapt. Boards are demanding clearer oversight. Regulators are sharpening expectations. At the same time, organizations are investing aggressively in AI, often without a disciplined roadmap for capturing value or managing enterprise exposure.

GenAI & Risk is a two-day executive certificate program designed to help leaders move beyond experimentation and into structured, enterprise-level execution. Participants learn how to unlock measurable business value from Generative AI while building the governance, risk, and oversight capabilities required to scale it with confidence. The program bridges strategy and control, balancing innovation with accountability, speed with discipline, and ambition with defensible risk management.

Designed for professionals responsible for AI initiatives, enterprise risk, compliance, or executive oversight, the program delivers practical frameworks for prioritizing use cases, sequencing investments, modernizing governance structures, and integrating AI into enterprise risk management (ERM). Participants leave better equipped to strengthen executive decision-making, increase board-level confidence, and deploy AI initiatives strategically, responsibly, and sustainably.

Program details

Next Cohort: May 14-15, 2026

Location: 100% Synchronous Online, plus networking dinner in Washington, DC, for local registrants

Daily: 8:30 a.m. to 3:30 p.m.

Audience: Individual contributors to GenAI initiatives, managers of GenAI implementations, and personnel and leadership in oversight roles for managing GenAI risk

Tuition: $1,495 including dinner

Contact: rhsmith-execed@umd.edu for information and one-day registration & payment options

Register now Get Brochure

Who is this for?

This program is for anyone asking the following questions:

  • How can I identify high-value use cases for generative AI?
  • How should I prioritize generative AI projects?
  • How can I garner internal support for my top-priority use cases?
  • How can I identify and manage generative AI risk?
  • How can I instill governance to effectively manage the risk of generative AI initiatives?
  • How can I find professionals to form a community of practice around generative AI and risk?

Valuable outcomes

  • Learn from senior industry risk practitioners and academic thought leaders who have been working in the AI space for decades.
  • Understand what tools and practices strengthen governance and risk infrastructure to leverage AI for maximum impact.
  • Build AI risk management skills through applying lessons learned from real-world case studies.
  • Gain critical insights about how to execute an AI strategic transformation plan.

Networking dinners: Join professionals in the Washington, D.C., metro area for dinner and cultivate a peer network to share experiences and lessons learned from AI implementations.

Certification: Receive a certificate of completion from the University of Maryland.

Certificate Sample

Faculty

Balaji PadmanabhanBalaji Padmanabhan, Ph.D.
Associate dean, strategic initiatives
Director, Center for AI in Business

Joe MatteyJoe Mattey, Ph.D.
SERC risk expert
Former chief model risk officer, Fannie Mae and USAA

Cliff RossiCliff Rossi, Ph.D.
Director, Smith Enterprise Risk Consortium
Professor of the practice
Former chief risk officer, Citigroup Consumer Lending

Evan SekerisEvan Sekeris, Ph.D.
Senior vice president, Bank Policy Institute
Former chief model risk officer, Capital One

Program agenda

Day 1

Thursday, May 14, 8:30 a.m.-3:30 p.m.

Introduction to generative AI terminology, strategy and risk
Understand foundations of generative AI and agentic systems and what firms are doing to unlock value creation

What successful firms do to create value
Understand the building blocks needed to be successful

Sequencing considerations for generative AI initiatives
A framework for sequencing of generative AI implementation

Effective AI governance and risk management
Understand risks accentuated by AI, how to mitigate them, and how to make decisions on when to proceed

Facilitated reflections: Value creation and prioritization
Identify how consideration of prior module content affects scope and prioritization of participants’ own generative AI use cases and their strategy for navigating the governance structure for their organization

Day 2

Friday, May 15, 8:30 a.m.-3:30 p.m.

Case studies of generative AI risk
Understand risk in generative AI and agentic systems through case studies

What are institutions and regulators doing about AI?
Understand the competitive landscape and regulatory expectations for AI

Does modernized risk management include AI use cases?
Predict, both technologically and from a business perspective, what is coming and the timing of capability readiness for the development of a risk management modernization strategy

Framework and best practices for managing risk in generative AI
Understand roles in AI transformation, particularly risk management roles that are disrupted and need to be reengineered; review AI risk management frameworks to help you design your own framework

Facilitated reflections: Managing generative AI risk
Reflect on the workshop and how it might influence actions going forward, operationally and strategically

Register now Get Brochure

Brought to you by: Robert H. Smith School of Business Office of Executive Education and SERC (Smith Enterprise Risk Consortium)

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