Beyond Automation: AI and the Human Value of Sell-Side Analysts

• 成果类型: Article; Early Access
• 署名作者: Shanthikumar, Devin; Yoo, Il Sun
• 署名单位: University of California System; University of California Irvine; Singapore Management University
• 刊物名称: JOURNAL OF ACCOUNTING RESEARCH
• ISSN/ISSBN: 0021-8456; 1475-679X
• DOI: 10.1111/1475-679x.70083
• 发表日期: 2026-08-19
• 关键词: Artificial intelligence; ai; Machine Learning; Sell-side analysts; Forecast

摘要

We examine how analysts' information acquisition and processing differ when analysts have access to AI resources, focusing on investment banks' AI investments. We propose and test a two-step framework, which is informed by in-depth interviews with analysts. First, consistent with AI facilitating automation-assisted public information processing, we show that AI investments are associated with more timely earnings forecasts following 10-K filings, particularly after the implementation of iXBRL, which increases the machine readability of filings. Second, we show that analysts reallocate the time and capacity freed by automation toward acquiring and incorporating private information, supported by several sets of evidence: AI investments (1) are associated with higher quality and bolder earnings forecasts, particularly when private information is more important and accessible to analysts; (2) are associated with an expansion of analyst coverage to new firms and industries; and (3) are associated with higher information-seeking efforts, particularly greater participation in earnings conference calls. Additionally, exploiting the launch of AskResearchGPT at Morgan Stanley, an in-house generative AI designed for research, we find results consistent with our main analyses. Overall, our study provides insights into the potential for AI to reshape the human value of sell-side analysts.