Driving Business Value with Generative AI: Strategy, Governance, and Risk

Why This Program Matters Now and How It Delivers

AI is no longer experimental. It is operational. Organizations across industries are deploying Generative AI tools at speed, yet governance models, risk frameworks, and oversight structures are struggling to keep pace. Boards expect clearer accountability. Regulators are refining expectations. Competitive pressure is rising. Success now depends not just on adopting AI, but on deploying it strategically, responsibly, and at scale.

This two-day executive certificate program is designed to address exactly that challenge. Participants gain the frameworks and practical tools needed to align AI initiatives with measurable business value, anticipate regulatory scrutiny, modernize enterprise risk management for AI-specific risks, and position risk functions as strategic enablers of innovation rather than barriers to progress.

Day 1: GenAI Value Creation & Strategic Prioritization focuses on building the front end of a successful AI strategy. Participants learn how to identify high-impact use cases, sequence initiatives based on value and feasibility, align stakeholders, and define the evolving roles of AI and human expertise. The result is a structured roadmap for AI deployment that balances speed, return, and organizational readiness.

Day 2: GenAI Governance & Risk Management Strategy addresses the oversight and accountability required to sustain AI transformation. Participants examine AI-specific risks, regulatory expectations, and the evolution of traditional model and operational risk frameworks. They leave with actionable governance models, oversight structures, and modernization strategies aligned with board-level expectations and enterprise resilience.

Across both days, expert-led instruction, real-world case studies, and facilitated reflections ensure that insights translate directly into operational and strategic impact, equipping leaders to guide AI transformation with confidence while protecting their organizations and unlocking competitive advantage.

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.

Learn From Recognized Leaders in Risk and AI

Participants benefit from instruction by senior practitioners and thought leaders in enterprise risk management, regulatory oversight, and AI strategy — professionals who have shaped risk frameworks at leading financial institutions and policy organizations.

Balaji Padmanabhan
Associate Dean of Strategic Initiatives and Dean's Professor of Decisions, Operations & Information Technologies

Balaji Padmanabhan brings more than two decades of experience helping organizations apply data science, artificial intelligence, and machine learning to real operational and strategic challenges. His work focuses on designing AI systems that improve decision-making, automate complex processes, and scale reliably in enterprise environments.

Cliff Rossi
Professor of the Practice, Director, Smith Enterprise Risk Consortium, Executive-in-Residence

Cliff Rossi brings nearly 25 years of C-suite risk leadership experience at institutions including Citigroup, Washington Mutual, Countrywide Bank, Freddie Mac, and Fannie Mae. A nationally recognized expert in financial and enterprise risk, frequent Congressional witness, and advisor to banks and regulatory agencies, Dr. Rossi translates high-stakes real-world leadership experience into practical frameworks that senior executives can immediately apply.

Evan Sekeris
Senior Economist, Bank Policy Institute

Evan Sekeris is a Senior Economist at the Bank Policy Institute and a recognized expert in enterprise and operational risk. He began his career in bank supervision at the Federal Reserve Bank of Boston and later founded the Quantitative Analysis team at the Federal Reserve Bank of Richmond, providing him with deep insight into regulatory expectations and supervisory frameworks. After nearly a decade advising global financial institutions at Aon and Oliver Wyman, he now focuses on modernizing risk frameworks to address emerging challenges, including AI governance and model oversight.

Joe Mattey
Former Chief Model Risk Management Officer, Fannie Mae

Joe Mattey is a senior risk executive with more than 25 years of experience helping financial institutions and government organizations strengthen decision-making through advanced analytics, statistical modeling, and artificial intelligence. In executive leadership roles at several of the largest financial services institutions, he built enterprise-scale model development and risk management functions, overseeing governance frameworks that supported capital planning, stress testing, credit risk, and market risk oversight. A recognized expert in Enterprise Risk Management and Model Risk Management, Joe brings deep experience in aligning innovation with governance discipline.

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