Research Seminar
[Brown Bag] Next Frontiers of AI for Business Decision Making: Multimodality and Causality Meet with LLMs and Agentic AI by Prof. Xueming Luo, Fox School of Business at Temple University
| Abstract: | Abstract: Marketing, customer, employee, firm disclosure data have become increasingly multimodal, simultaneously conveying visual, auditory, and textual information. Most prior studies adopt a “signal-by-signal” AI approach, using LLM to extract visual, textual, and audio features separately. Yet consumers integrate facial expressions, gestures, vocal tone, and contextual cues to construct meaning. Ignoring these cross-modal interactions can therefore produce biased estimates and incomplete theoretical understanding. Furthermore, prior research often treats extracted visual, textual, and audio features as exogenous, overlooking endogeneity and unobserved confounders in unstructured data. Because creators strategically choose language, imagery, and vocal expressions, focal treatments may be confounded by latent factors such as design aesthetics, persuasion, authenticity, and audience targeting. Consequently, even LLM-based predictive reasoning AI models cannot reliably identify causal treatment effects from unstructured data. To address these limitations, I will introduce methodological frameworks that integrate advances from multisensory AI, multimodal foundation models, and emerging causal inference techniques for generative AI systems. Specifically, I will discuss state-of-the-art methods for modeling cross-modal interactions through attention mechanisms, multimodal representation learning, and modality fusion architectures, alongside recent developments in causal machine learning and representation-based deconfounding, so as to generate more credible causal inference from large-scale video, image, audio, and language data. Whether you are a PhD student, faculty member, or industry practitioner, this session will provide actionable insights into the next frontier of AI-powered research and practice for business decision making. |
| Date: | Sep 2 (Wed), 2026 2:00 pm - 3:30 pm |
| Time: | 2:00PM - 3:30PM |
| Venue: | LAU-6-207, Level 6, Lau Ming Wai Academic Building (LAU) |
| Details: | Biography: Xueming Luo is the Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy, and Professor of MIS, and Founder/ Director of the Global Institute for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. He is an interdisciplinary thought-leader in leveraging AI/ML algorithms, text/audio/image/video big data, econometrical methods, and field experiments to model, explain, and optimize digital marketing, customer analytics, brand value, social media, influencer marketing, mobile targeting, company strategies, platform economy, and social-political activism. Within marketing, he has been ranked as top 9th worldwide (#1 among all Chinese scholars) regarding Author Productivity in the Premier Marketing Journals (MkSc, JMR, JM, JCR) during 2014-2023. Outside of marketing, his research has been featured by premier journals in Information Systems (ISR and MISQ), Management, Strategy, and OM (MgSc, SMJ, AMJ, MSOM, POM). Xueming has over 32,000 citations on Google Scholar and is ranked top 2% researchers worldwide in business by Scopus citations. Xueming served as a guest Associate Editor of Journal of Marketing Research, Associate Editor of International Journal of Research in Marketing, and Journal of the Academy of Marketing Science. He also was on the editorial board of Marketing Science, Journal of Marketing, Journal of Marketing Research, and Academy of Management Journal. https://www.fox.temple.edu/directory/xueming-luo-tuf35198 |
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