For twenty-five years, I have worked at the intersection of governance, innovation, enterprise transformation, technology strategy, and institutional decision-making. Through that work, I observed a structural shift that traditional governance frameworks did not fully address: intelligent systems were no longer merely automating execution—they were beginning to shape judgment itself.
My engagement with artificial intelligence began much earlier. As an undergraduate engineering student, I wrote my thesis on how neural networks learn from error and improve their predictions—a method known as backpropagation. The technology was not yet commercially viable at scale. As computing power, data, and infrastructure advanced, AI moved from the laboratory into the operating fabric of the enterprise.
My thinking on governance was shaped at Yale University, where I studied corporate governance under Ira Millstein and Paul MacAvoy. Their work established governance as a discipline of authority, accountability, oversight, and institutional responsibility—not merely compliance. That foundation influenced how I approached strategy and transformation throughout my career.
As artificial intelligence became embedded across enterprise capabilities, it became clear that this technology differed fundamentally from earlier generations of enterprise systems. Traditional technologies largely executed rules and decisions established by people. Intelligent systems increasingly shape how choices are framed, which options receive attention, what thresholds apply, and when matters are escalated. Formal accountability may remain human even as practical discretion migrates into data, models, workflows, and system architecture.
Drawing on years of leading enterprise transformation in financial services, I recognized that advances in artificial intelligence were redistributing decision authority while accountability remained with people. That insight became the foundation for my book, Overruled: Governing the Intelligent Enterprise. Rather than asking how organizations should govern AI as a technology, the book asks how boards and executive leaders should govern the migration of decision authority as intelligence becomes embedded throughout the enterprise.
Today, I advise boards and executive leadership teams on governing enterprise transformation in the age of AI through board advisory, executive education, and leadership briefings. My work focuses on helping institutions govern the institutional consequences of embedded intelligence, including authority, capability transformation, operational dependence, and long-term stewardship.
Education:
MBA, Strategy & Finance — Yale University
MS, Electrical Engineering (Yale Fellowship Award) — Yale University
BE, Electrical Engineering (summa cum laude) — City College of New York
Executive Education:
Harvard Business School • MIT Sloan • Wharton • Berkeley Haas