Symposium on Artificial Intelligence in Marketing 2026
Academic Event for Researchers, Wisconsin School of Business
Monday, May 11 | 1:00pm – Wednesday, May 13 | 12:00pm
The Wisconsin School of Business at the University of Wisconsin-Madison is thrilled to host the 3rd Symposium on Artificial Intelligence in Marketing. The 2026 Symposium will be taking place from May 11, 1pm to May 13, 12pm in Madison, Wisconsin. The symposium focuses on modern AI applications in marketing, including:
- Deep Learning and Unstructured Data Analysis
- Generative AI in Marketing
- Human-AI collaboration
- Algorithmic Bias and Fairness
- Digital Twins
- Probabilistic Machine Learning and Computational Methods for Marketing
Email your questions to aimarketing@wsb.wisc.edu
Keynotes
Simon Blanchard
Simon Blanchard is the Dean’s Professor and Professor of Marketing at Georgetown University’s McDonough School of Business. His research spans a broad range of marketing methods, including survey design, controlled experiments, and econometric analysis of large datasets. As a methodologist, he brings flexibility and rigor to studying complex decision-making, often applied to how consumers navigate financial trade-offs and emerging technologies.
For a three year term beginning in April 2026, he will serve as co-editor of the Journal of Marketing Research. Previously, he served as Associate Editor at four journals (Journal of Marketing, Journal of Marketing Research, Journal of Consumer Research, and the International Journal of Research in Marketing) and has served on the AMA Academic Council. He still serves on the board of the INFORMS Society for Marketing Science.
Outside of academia, Professor Blanchard advises organizations on research design, surveys, marketing analytics, digital strategy, and fintech. He also serves as a subject-matter expert for the Analysis Group.
David Schweidel
David A. Schweidel is the Goizueta Chair in Business Technology and Professor of Marketing at Emory University’s Goizueta Business School. Schweidel received his B.A. in mathematics, M.A. in statistics, and Ph.D. in marketing from the University of Pennsylvania.
He has served on the faculty of the Wisconsin School of Business at the University of Wisconsin-Madison and Georgetown University’s McDonough Business School. His research has appeared in leading business journals including Journal of Marketing, Journal of Marketing Research, Marketing Science, Management Science, and Harvard Business Review. Schweidel is co-author of Social Media Intelligence and author of Profiting from the Data Economy.
His current research focuses on consumers’ use of new technologies, and how these technologies can be leveraged by marketers. In addition to his research, he has consulted for companies including eBay, Airbnb, and Thumbtack.
Schedule
Monday, May 11th
| Time | Session Title |
|---|---|
| 1:00 PM – 2:00 PM | Welcome + AI Hub Keynote |
| 2:00 PM – 3:00 PM | MSI Industry Panel |
| 3:00 PM – 3:20 PM | Break |
| 3:20 PM – 5:00 PM | Session: Leveraging AI for Economic Value and Personalization |
| 5:00 PM – 5:10 PM | Break |
| 5:10 PM – 7:00 PM | Reception |
Tuesday, May 12th
| Time | Session Title |
|---|---|
| 8:00 AM – 9:00 AM | Breakfast |
| 9:00 AM – 10:00 AM | Keynote 1 |
| 10:00 AM- 10:20 AM | Break |
| 10:20 AM – 12:00 PM | Session: Understanding Content & AI-Assisted Creativity |
| 12:00 PM – 1:30 PM | Lunch + Keynote 2 |
| 1:30 PM – 2:00 PM | Break |
| 2:00 PM – 3:15 PM | Session: Modeling Consumers with AI |
| 3:15 PM – 3:45 PM | Break |
| 3:45 PM – 5:00 PM | Session: Search, News & Recommendations |
Wednesday, May 13th
| Time | Session Title |
|---|---|
| 8:00 AM – 9:00 AM | Breakfast |
| 9:00 AM – 10:40 AM | Session: Causal Inference & Experimental Design |
| 10:40 AM- 11:00 AM | Break |
| 11:20 AM – 12:15 PM | Session: Methodological Advances in Measurement, Optimization, and Estimation |
Registration
Please register using the link below. Note that we have a very limited number of spots.
Deadline: April 23rd.
Regular Attendees: $250.00
Includes access to all sessions, materials, and meals.
PhD Students & Scientific Review Committee: $100.00
Includes access to all sessions, materials, and meals.
Internal Employees/PhD Students: (Wisconsin School of Business only)
Registration covered by internal funding
The confirmation email is usually sent within 15 minutes.
Sessions
| Leveraging AI for Economic Insight and Personalization | |
| (Mis)Measuring the Drivers of Ad Performance: A User Guide for LLMs in Empirical Creative Research | Gijs Overgoor, Samsun Knight, Yakov Bart |
| Economic Value of Visual Product Characteristics | Vineet Kumar, Ankit Sisodia |
| Learning Heterogeneity from Unstructured Data: An Application to Chatbot Personalization | Khai Chiong, Ryan Dew |
| Can Explanations Improve Recommendations? A Joint Optimization with LLM Reasoning | Yuyan Wang, Pan Li, Minmin Chen |
Understanding Content & AI-Assisted Creativity | |
| Large Language Models as Engines of Understanding: Interpretable Discriminative Features from Text | Tong Wang, Yiqing Xu, Leo Yang |
| Modeling Serialized Content Consumption: Adversarial IRL for Dynamic Discrete Choice | Peter S. Lee, K. Sudhir, Tong Wang |
| Content-Aligned Cover Design: A Multimodal Deep Learning Approach to Understanding and Enhancing Media Cover Success | Yijing Xu, Remi Daviet, Maria Hademer |
| Guided Creativity: AI Intermediation for Enhancing Quality and Originality in Visual Design | Xuekang Wu, Guy Aridor, Artem Timoshenko |
Modeling Consumers with AI | |
| Predicting Behaviors with Large Language Model (LLM)-Powered Digital Twins of Consumers | Bingqing Li, Qiuhong (Owen) Wei, Xin (Shane) Wang |
| Bayesian Machine Learning Approach for Modeling Dynamic Consumer Preferences | Hengxu Lin, Kohei Onzo, Asim Ansari |
| Collaborative Intelligence: Reconstructing Invisible Consumers with a Fine-Tuned LLM and Multi-Task Learning Framework | Jiyeon Hong, Alice Li, Qing Liu |
Search, News & Recommendations | |
| Addressing Consumers’ Sensitive Attributes in Product Recommendations: An Explainable AI Recommendations System Approach | Piyush Anand |
| Generative Search: Evidence from a Large-Scale Field Experiment | Yuting Zhu, Shuang Zheng |
| The Impact of LLMs on Online News Consumption and Production | Hangcheng Zhao, Ron Berman |
Causal Inference & Experimental Design | |
| Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach | George Gui, Seungwoo Kim |
| GENI: GenAI-Assisted Inference for Emotional Ad Copy | Xinyue Zhao, Xueming Luo |
| A Bayesian Latent-Factor Framework for Causal Decomposition in High-Dimensional Experiments | Khaled Boughanmi, Raghuram Iyengar, Young-Hoon Park |
| Personalized Policy Learning through Discrete Experimentation: Theory and Empirical Evidence | Zhiqi Zhang, Zhiyu Zeng, Ruohan Zhan, Dennis Zhang |
Methodological Advances in Measurement, Optimization, and Estimation | |
| Pre-Training Estimators for Structural Models: Application to Consumer Search | Zhenling Jiang, Yanhao Wei |
| TextBO: Bayesian Optimization in Language Space for Eval-Efficient Self-Improving AI | Enoch Hyunwook Kang, Hema Yoganarasimhan |
| To Err Is Human; To Annotate, SILICON? Reducing Measurement Error in LLM Annotation | Xiang Cheng, Raveesh Mayya, Joao Sedoc |
Lodging
We have partnered with the The Madison Concourse Hotel to provide rooms at affordable rate for both nights (5/11 and 5/12) at $169 per night.
These prices will be available until April 24, 2026 or until rooms are sold out (whichever comes first). For complimentary airport shuttles, 4:30AM-10:30PM, call 608-257-6000.
To reserve a room, follow the following link.
Location
Symposium Chairs
Scientific Review Committee
Papers are reviewed by at least two members of the scientific committee.
Co-chairs: Ishita Chakraborty, Remi Daviet
Members:
Wenjia Ba, University of British Columbia
Khaled Boughanmi, Cornell
Emaad Manzoor, Cornell
Gijs Overgoor, Southern Methodist University
Yuyan Wang, Stanford
Mengxia Zhang, Western University (Ivey)
