Sunghee Yun (He/Him)

Co-Founder & CTO @ Erudio Bio, Inc., Co-Founder & Leader & Chair of Silicon Valley AI Nexus (AI Nexus), Advisor @ Korean American Semiconductor Professional Alliance (KASPA), CGO / Global Managing Partner @ LULUMEDIC, KFAS-Salzburg Global Leadership Initiative Fellow @ Salzburg Global Seminar, AI-Korean Medicine Integration Initiative Task Force Member @ The Association of Korean Medicine, Director of AI Semiconductor @ K-BioX, Visiting Professor @ Sogang University, Advisory Professor @ DGIST, Global Advisory Board Member @ Innovative Future Brain-Inspired Intelligence System Semiconductor of Sogang University, and Network Expert @ Gerson Lehrman Group

Abstract

The emergence of Artificial Intelligence (AI) as a general-purpose technology is fundamentally restructuring the economic foundations of modern business, yet most executives and business leaders lack the frameworks necessary to understand AI’s true implications for competitive strategy, market structure, and value creation. This seminar provides business school students and future leaders with essential economic insights into how AI is not merely automating existing processes, but creating entirely new paradigms for how firms compete, how markets organize, and how value flows through economic systems. Drawing from cross-industry experience spanning Silicon Valley startups, Fortune 500 corporations, and cutting-edge research institutions, this session explores the economic mechanisms through which AI transforms business models—from semiconductor manufacturing and e-commerce to biotechnology and financial services—revealing patterns that transcend individual sectors and signal broader structural changes in the global economy.

The first part of the presentation examines AI’s impact on traditional economic concepts including economies of scale, network effects, and competitive moats. We’ll explore how AI fundamentally alters cost structures by converting fixed costs into marginal improvements, how it creates new forms of increasing returns through data network effects and model performance scaling, and how it enables winner-take-most dynamics in ways that differ sharply from previous technology revolutions. Through detailed case studies of companies successfully leveraging AI for competitive advantage—from Amazon’s supply chain optimization to biotech firms accelerating drug discovery—students will understand the specific mechanisms by which AI creates defensible business positions. We’ll also examine why many AI initiatives fail to deliver economic value, analyzing the gap between technological capability and business model innovation, and providing frameworks for evaluating when AI investments generate genuine competitive advantage versus merely keeping pace with industry standards.

The economic transformation extends beyond individual firm strategy to reshape entire market structures and industry boundaries. This section addresses how AI enables new forms of market organization, from platform ecosystems that orchestrate multi-sided value creation to vertical integration strategies that capture AI-generated insights across the value chain. We’ll examine the economics of AI development itself—the massive capital requirements for frontier model training, the talent markets for AI expertise, and the venture capital dynamics driving AI startup valuations. Particular attention will be paid to the semiconductor industry’s role as the foundational layer of the AI economy, exploring how chip design, manufacturing capacity, and supply chain dynamics create bottlenecks and opportunities that ripple through all AI-dependent sectors. Students will gain frameworks for understanding market concentration trends, the conditions under which AI favors incumbents versus enabling disruption, and how regulatory approaches across different jurisdictions create varying competitive landscapes for AI-driven businesses.

Beyond market structure, AI poses profound questions about the nature of economic value creation in an era where intelligence itself becomes abundant and cheap. We’ll explore the paradox of AI simultaneously increasing productivity while potentially commoditizing cognitive labor, examining how firms can capture value when powerful AI capabilities become widely accessible. The discussion addresses critical strategic questions: How do businesses build sustainable advantages when AI models can be replicated? What new scarcity factors emerge as intelligence becomes abundant? How should firms think about human capital strategy when AI reshapes the productivity frontier? Drawing from behavioral economics and organizational theory, we’ll examine how AI changes decision-making processes within firms, the challenges of AI-human collaboration, and the organizational capabilities required to effectively deploy AI systems. This section provides students with practical frameworks for navigating the transition from AI as a technology project to AI as a core business capability, including investment prioritization, talent development, and organizational design considerations.

The seminar concludes with forward-looking analysis of AI’s trajectory and its implications for business leadership, examining both extraordinary opportunities and critical challenges facing the next generation of managers. We’ll address the “hype versus reality” question by analyzing economic indicators—investment flows, adoption rates, productivity measurements, and market valuations—to provide students with tools for distinguishing genuine transformation from speculative excess. The discussion encompasses AI’s implications for global competition, including how different national approaches to AI development create varying business environments, and how firms should navigate an increasingly fragmented technological landscape. Ultimately, this session prepares business students not just to understand AI as a technology, but to lead organizations through the economic transformation it enables—developing strategic thinking that combines technological literacy with deep understanding of competitive dynamics, market forces, and value creation in the age of intelligent machines. Students will leave equipped with frameworks for making sound business decisions in an AI-driven economy, positioning them to become leaders who can harness AI’s potential while navigating its complexities and building organizations that thrive amid unprecedented technological change.