When AI Rewrites the Rules: Rethinking Business Research, Education, and Practice
Prof. Philip Renyu ZHANG
Associate Professor,
The Chinese University of Hong Kong
Date: 24 April 2026 (Friday)
Time: 10:30-12:00
Venue: E22-G008
Host: Prof. Li XIAO, Associate Professor in Business Intelligence and Analytics
Abstract
The launch of ChatGPT on November 30, 2022 marked the opening of a new wave of generative AI revolution. The sudden emergence of DeepSeek in early 2025 further advanced the democratization of AI, sparking a global sensation. By 2026, the maturation of AI Agent technology has brought both productivity gains and widespread anxiety about its impact on labor markets. As a business researcher and educator, I have spent the past three and a half years thinking about and experimenting with how to respond to the disruption of AI technology by: (1) producing more meaningful research, (2) cultivating students better equipped for an AI-native era, and (3) generating real-world business impact. In this talk, I will share my personal explorations at the intersection of AI and business research, education, and practice from three perspectives, research, teaching, and commercialization, along with the insights, challenges, and lessons I have encountered along the way. On the research front, I will discuss how AI technology can empower business research (reference: my PhD course AI for Business Research, https://github.com/rphilipzhang/AI-PhD-S26). On the teaching front, I will share my experience developing business AI curricula suited to the current era. On the practice front, I will share what it takes to build products that meet the demands of an AI-driven market.
Speaker
Renyu (Philip) Zhang has been an Associate Professor (with tenure) at the Department of Decisions, Operations and Technology, The Chinese University of Hong Kong Business School since September 2022. He is also an economist and Tech Lead at Kwai, one of the world’s largest online video-sharing and live-streaming platforms. Philip’s recent research applies AI and data science to empower business decision making under the emerging trends in technology, marketplaces, and society. He develops AI and data science methodologies (large language models, machine learning, causal inference, and data-driven optimization) to evaluate and optimize the operations strategies in the contexts of online platforms and marketplaces, sharing economy, and social networks, especially their recommendation, advertising, pricing, and matching policies. His research works have appeared in top journals such as Management Science, Operations Research, and Manufacturing & Service Operations Management, and have been recognized by various research awards of the INFORMS and POMS communities. His research projects have been funded by various funding agencies including Hong Kong RGC Research Fellow Scheme, NSFC (青B/优青), HK RGC, SMEC, STCSM, Tencent, Alibaba, and Didi. Philip serves as an Associate Editor for Operations Research and Manufacturing & Service Operations Management, and a Senior Editor for Production and Operations Management. He has also developed data science and economics frameworks to evaluate and optimize the user growth strategy and the platform ecosystem of Kuaishou. Prior to joining CUHK, Philip was an Assistant Professor of Operations Management at New York University Shanghai between 2016 and 2022.
All are welcome!
