The Impact of Artificial Intelligence Adoption on Corporate Default Risk: Empirical Evidence Based on Large Language Models

Against the backdrop of rapid advances in digital technologies and growing uncertainty in the business environment, artificial intelligence (AI) offers firms new opportunities to strengthen risk identification, improve managerial decision-making, and mitigate default risk. Using firm-level data from Chinese A-share listed companies over the period 2009–2024, this study empirically examines the relationship between AI adoption and corporate default risk. The results indicate that AI adoption is associated with a significant reduction in corporate default risk. This finding remains robust to alternative fixed-effects specifications, different levels of standard-error clustering, and the exclusion of observations from periods affected by major external shocks. Heterogeneity analyses further reveal that the negative association is particularly pronounced among firms in non-high-tech industries and those located in eastern and central China. By examining AI adoption from a corporate risk management perspective, this study extends the literature on the economic consequences of AI adoption and provides firm-level empirical evidence on the role of digital technologies in mitigating financial risk. The findings also offer policy implications for integrating AI into corporate management practices and strengthening firms’ risk governance capabilities.

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Publication Details

Journal
Innovation in Science and Technology
Published
2026-11-02
DOI
https://doi.org/10.63593/ist.2788-7030.2026.09.007
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impact of Artificial Intelligence Adoption on Corporate Default Risk: Empirical Evidence Based on Large Language Models

Xiangchun Liu, Yuecong Xing, Chuhan Su
5 links
Innovation in Science and Technology
Financial Distress and Bankruptcy Prediction
article

The Impact of Artificial Intelligence Adoption on Corporate Default Risk: Empirical Evidence Based on Large Language Models

Xiangchun Liu, Yuecong Xing, Chuhan Su
article en

Abstract

Against the backdrop of rapid advances in digital technologies and growing uncertainty in the business environment, artificial intelligence (AI) offers firms new opportunities to strengthen risk identification, improve managerial decision-making, and mitigate default risk. Using firm-level data from Chinese A-share listed companies over the period 2009–2024, this study empirically examines the relationship between AI adoption and corporate default risk. The results indicate that AI adoption is associated with a significant reduction in corporate default risk. This finding remains robust to alternative fixed-effects specifications, different levels of standard-error clustering, and the exclusion of observations from periods affected by major external shocks. Heterogeneity analyses further reveal that the negative association is particularly pronounced among firms in non-high-tech industries and those located in eastern and central China. By examining AI adoption from a corporate risk management perspective, this study extends the literature on the economic consequences of AI adoption and provides firm-level empirical evidence on the role of digital technologies in mitigating financial risk. The findings also offer policy implications for integrating AI into corporate management practices and strengthening firms’ risk governance capabilities.

Innovation in Science and TechnologyVol. 5(3)
Minzu University of China (CN), King's College London (GB)
Industry, innovation and infrastructure, Decent work and economic growth
Openalex Percentile: Top 8%
Financial Distress and Bankruptcy Prediction
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The Impact of Artificial Intelligence Adoption on Corporate Default Risk: Empirical Evidence Based on Large Language Models — Xiangchun Liu, Yuecong Xing, et al. · Innovation in Science and Technology (2026) | TGRS Research Map | TGRS