Visual Information and AI Divide: Evidence from Corporate Executive Presentations

55 Pages Posted: 26 Jun 2023 Last revised: 18 Jul 2023

See all articles by Sean Cao

Sean Cao

University of Maryland - Robert H. Smith School of Business

Yichen Cheng

Georgia State University

Meng Wang

University of South Florida - Muma College of Business

Yusen Xia

Georgia State University - Robinson College of Business

Baozhong Yang

Georgia State University - J. Mack Robinson College of Business

Date Written: November 17, 2022

Abstract

This paper constructs and studies a novel data set comprised of corporate executive presentations, which provide unique visual information about firms' products and operations. We explore the value of visual information in presentations and examine how market participants respond to such information. We extract visual features from presentation images with large image models and find not all images have the same implications for firm value. Forward-looking operational information is associated with higher short-term abnormal returns and long-term operational performance while other types of images are not. We also examine whether the rise of alternative big data and AI creates a potential AI divide among market participants. We find AI-equipped institutional investors respond strongly to visual signals, whereas retail investors and traditional institutional investors face marginalization on the playing field in the age of AI and big data.

Keywords: JEL Classification: D83, G12, G14, G23, G30 Machine Learning, Artificial Intelligence, FinTech, Corporate Presentation, Image Analysis, Textual Analysis, Information and Market Efficiency, Institutional Investors, Investment

JEL Classification: D83, G12, G14, G23, G30

Suggested Citation

Cao, Sean S. and Cheng, Yichen and Wang, Meng and Xia, Yusen and Yang, Baozhong, Visual Information and AI Divide: Evidence from Corporate Executive Presentations (November 17, 2022). Available at SSRN: https://ssrn.com/abstract=4490834 or http://dx.doi.org/10.2139/ssrn.4490834

Sean S. Cao

University of Maryland - Robert H. Smith School of Business ( email )

College Park, MD 20742-1815
United States

Yichen Cheng

Georgia State University ( email )

35 Broad Street
Atlanta, GA 30303-3083
United States

Meng Wang (Contact Author)

University of South Florida - Muma College of Business ( email )

Tampa, FL 33620
United States

Yusen Xia

Georgia State University - Robinson College of Business ( email )

35 Broad Street
Atlanta, GA 30303-3083
United States

Baozhong Yang

Georgia State University - J. Mack Robinson College of Business ( email )

35 Broad St NW
Atlanta, GA Ga 30303-3083
United States
4044137350 (Phone)

HOME PAGE: http://sites.google.com/view/baozhongyang/home

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