Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks

Artificial intelligence (AI) has been increasingly deployed in business operations over the past decade, whereas direct evidence of its effectiveness in uncertain contexts is limited. Our work examines the contribution of AI to corporate resilience under natural disaster shocks, particularly concentrating on AI-using and goods-producing firms. We measure firm AI investment by the cumulative AI-relevant skills extracted from a comprehensive job posting database and firm resilience by the changes in corporate valuation in response to operational shocks. Evidence suggests that AI generates resilience: An average firm that equips 2.4% of total jobs to be AI-related could approximately recover the full damage of disasters reflected in corporate valuation over a short event window. From the product function test, we find that resilience is attributable to the moderating effect of AI on the damaged input responsiveness under the volatile production environment. Our analyses further reveal a pressing phenomenon: Although underperforming firms could benefit more from an additional unit of AI investment, the realized productivity is notably restrained due to a lack of complementary organizational designs. Our findings provide managerial implications regarding the interplay between environmental conditions and firm investments in both AI technology and complementary infrastructures.

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Publication Details

Journal
Information Systems Research
Published
2025-03-25
DOI
https://doi.org/10.1287/isre.2022.0440
Citations
19
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
42.30
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article

Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks

Hongchuan Shen, Jing Wu, Miaozhe Han, Xiaoquan Zhang
19 citations
Information Systems Research
Supply Chain Resilience and Risk Management
42.30
article

Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks

Hongchuan Shen, Jing Wu, Miaozhe Han, Xiaoquan Zhang
article en
19 citations

Abstract

Artificial intelligence (AI) has been increasingly deployed in business operations over the past decade, whereas direct evidence of its effectiveness in uncertain contexts is limited. Our work examines the contribution of AI to corporate resilience under natural disaster shocks, particularly concentrating on AI-using and goods-producing firms. We measure firm AI investment by the cumulative AI-relevant skills extracted from a comprehensive job posting database and firm resilience by the changes in corporate valuation in response to operational shocks. Evidence suggests that AI generates resilience: An average firm that equips 2.4% of total jobs to be AI-related could approximately recover the full damage of disasters reflected in corporate valuation over a short event window. From the product function test, we find that resilience is attributable to the moderating effect of AI on the damaged input responsiveness under the volatile production environment. Our analyses further reveal a pressing phenomenon: Although underperforming firms could benefit more from an additional unit of AI investment, the realized productivity is notably restrained due to a lack of complementary organizational designs. Our findings provide managerial implications regarding the interplay between environmental conditions and firm investments in both AI technology and complementary infrastructures.

Information Systems ResearchVol. 36(4)
Chinese University of Hong Kong (HK), Hong Kong University of Science and Technology (HK), University of Macau (MO)
Openalex Percentile: Top 0%
Supply Chain Resilience and Risk Management
42.30
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Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks — Hongchuan Shen, Jing Wu, et al. · Information Systems Research (2025) | TGRS Research Map | TGRS