Generative AI and investor processing of financial information

• 成果类型: Article
• 署名作者: Blankespoor, Elizabeth; Croom, Joe; Grant, Stephanie M.
• 署名单位: University of Washington; University of Washington Seattle; Indiana University System; Pennsylvania State System of Higher Education (PASSHE); Indiana University Bloomington; Indiana University of Pennsylvania; University of Illinois System; University of Illinois Urbana-Champaign
• 刊物名称: JOURNAL OF ACCOUNTING & ECONOMICS
• ISSN/ISSBN: 0165-4101; 1879-1980
• DOI: 10.1016/j.jacceco.2026.101908
• 发表日期: 2026-11
• 页码: 101908
• 关键词: generative AI; Information processing; Investment decisions; RETAIL INVESTORS; market impact; TECHNOLOGY; complexity; field

摘要

This paper provides archival and survey evidence on retail investor use of Generative AI (GenAI). Our archival analysis examines over 400,000 investor queries to a major brokerage's GenAI chatbot. Investors most often use GenAI to help interpret and contextualize financial information and market movements, and for additional tasks including stock screening and streamlining complex research. As time with the tool grows, usage shifts from stock screening and high-level company assessments toward detailed monitoring and interpretation of firm news. Our survey of over 2,000 retail investors explores who adopts GenAI and why. Nearly half report using GenAI, primarily to accelerate and simplify information processing. More sophisticated retail investors lead adoption, deploying GenAI for more complex tasks and diverse information sources. Concerns about response quality and data privacy represent the biggest obstacles to further adoption. Heterogeneous adoption highlights the need for research into GenAI's impact on investor behavior and market dynamics.