AX Driven by Predictive AI: Transforming Decision-Making Architecture
Session Overview
The true value of AI extends far beyond simple task automation β it lies in enabling better, faster, and more informed decision-making. This session explores how predictive AI is reshaping enterprise decision-making architectures and driving meaningful AI Transformation (AX).
Through real-world industry cases, including demand forecasting, price prediction, and risk assessment, the session highlights the growing importance of data-driven decision-making. It also examines the differences between generative AI and predictive AI, along with strategies for leveraging their complementary strengths to create greater business value.
Furthermore, the session presents the new decision-making frameworks and AX strategies that organizations must adopt in the era of AI agents. Participants will gain insights into how businesses can build future-ready capabilities and secure sustainable competitive advantage in an increasingly AI-driven world.
Speaker
Doohee Chung is the CEO of Impactive AI and an Associate Professor in the School of AI Convergence at Handong Global University, where he actively contributes to AI research and education. He earned his Ph.D. in Technology Management from Seoul National University and spent a decade at the Samsung Economic Research Institute (SERI) and SERICEO. Bridging academia and industry, he has served as Editor-in-Chief of MIT Technology Review Korea and as an AI Advisory Professor for LG Group. His work focuses on helping organizations harness emerging technologies to drive innovation and business transformation.