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Generative AI in Capital Markets: Information Production, Dissemination, and Processing

Sean Cao¹; Wilbur Chen²; Guang Ma³; Suraj Srinivasan⁴

¹ Robert H. Smith School of Business University of Maryland · ² Hong Kong University of Science and Technology · ³ Rutgers Business School, Rutgers University · ⁴ Harvard Business School, Harvard University

ABSTRACT We synthesize evidence from six papers presented at the 2025 Journal of Accounting Research Conference on how generative artificial intelligence (GenAI) is reshaping capital‐market information flows. Our discussion is organized around an economic framework with three layers: information production by firms and accounting professionals, information dissemination through intermediaries, and information processing by investors. Across these layers, the conference papers show that GenAI can lower preparation costs, improve intermediary productivity, and reduce investors’ processing costs. At the same time, they point to a common constraint: whether GenAI improves the information environment depends critically on information verification costs. We also highlight gaps in current evidence and outline future research opportunities within and across the three layers.

DOI

10.1111/1475-679x.70061

Volume

64 (3)

Pages

1427-1450

Language

en

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BibTeX

Sources

crossref openalex