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題名 Does corporate AI adoption improve investment efficiency? Evidence from textual analysis of 10-K filings
作者 李佳玲
Hsu, Fu-Hsuan;Lee, Chia-Ling;Gong, Fang;Chuang, Chih-Yu
貢獻者 會計系
關鍵詞 Investment efficiency; Exploitation AI; Exploration AI; Textual analysis; Agency problems
日期 2026-09
上傳時間 1-Sep-2026 14:14:02 (UTC+8)
摘要 We examine the impact of the adoption of corporate artificial intelligence (AI) on investment efficiency using a novel text-based measure from U.S. 10-K disclosures (2012–2023). We find that AI adoption is positively and significantly associated with investment efficiency. This improvement is primarily driven by a reduction in overinvestment, suggesting that AI reduces uncertainty and agency-driven inefficiencies. The efficiency gains are concentrated in exploitation AI applications embedded in operational workflows, whereas exploration AI yields no significant impact. Furthermore, the benefits are more pronounced for firms characterized by higher information asymmetry and greater marketing intensity, highlighting AI’s role in navigating opaque and data-rich environments. Our findings are robust to an industry-level AI exposure measure based on occupation-level data, capturing firms’ exposure to AI-driven technological demand. Overall, AI enhances capital allocation by serving as a disciplining mechanism within routine decision-support systems.
關聯 Finance Research Letters, Vol.107, 110366
資料類型 article
DOI https://doi.org/10.1016/j.frl.2026.110366
dc.contributor 會計系
dc.creator (作者) 李佳玲
dc.creator (作者) Hsu, Fu-Hsuan;Lee, Chia-Ling;Gong, Fang;Chuang, Chih-Yu
dc.date (日期) 2026-09
dc.date.accessioned 1-Sep-2026 14:14:02 (UTC+8)-
dc.date.available 1-Sep-2026 14:14:02 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2026 14:14:02 (UTC+8)-
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=184652-
dc.description.abstract (摘要) We examine the impact of the adoption of corporate artificial intelligence (AI) on investment efficiency using a novel text-based measure from U.S. 10-K disclosures (2012–2023). We find that AI adoption is positively and significantly associated with investment efficiency. This improvement is primarily driven by a reduction in overinvestment, suggesting that AI reduces uncertainty and agency-driven inefficiencies. The efficiency gains are concentrated in exploitation AI applications embedded in operational workflows, whereas exploration AI yields no significant impact. Furthermore, the benefits are more pronounced for firms characterized by higher information asymmetry and greater marketing intensity, highlighting AI’s role in navigating opaque and data-rich environments. Our findings are robust to an industry-level AI exposure measure based on occupation-level data, capturing firms’ exposure to AI-driven technological demand. Overall, AI enhances capital allocation by serving as a disciplining mechanism within routine decision-support systems.
dc.format.extent 105 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Finance Research Letters, Vol.107, 110366
dc.subject (關鍵詞) Investment efficiency; Exploitation AI; Exploration AI; Textual analysis; Agency problems
dc.title (題名) Does corporate AI adoption improve investment efficiency? Evidence from textual analysis of 10-K filings
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.frl.2026.110366
dc.doi.uri (DOI) https://doi.org/10.1016/j.frl.2026.110366