AI and Immunity to the COVID-19 Pandemic

作者
Abhishek Bhatia,Nikhil Madan,Deepa Mani,Shekhar Tomar
出处
期刊:Production and Operations Management [Wiley]
标识
DOI:10.1177/10591478251392711
摘要

We evaluate economic immunity to the COVID-19 pandemic accorded by a sector’s exposure to artificial intelligence (AI). Using an event study design, we causally estimate the impact of AI industry exposure (AIIE) on shifts in economic activity following the first pandemic-induced lockdown in India. We use payments data from one of India’s largest payment gateways and find that a one-standard-deviation increase in AIIE arrests the post-pandemic decline in industry payments by a third. High AIIE of neighboring sectors further improves a sector’s economic resilience, emphasizing the importance of supply chain partners in technology adoption and change. Further analyses speak to the mechanisms underlying the documented impact of AI on economic activity. Notably, we present evidence suggesting that the observed effects of AI are distinct from those attributable to IT investments or digitization, that AI investments are associated with superior information capabilities prior to the pandemic that arguably enabled agility and responsiveness, and that AI-enabled adaptation occurs in a manner that complements labor rather than displacing it. We discuss the implications of our findings in terms of the assessment of the business value of AI and management of disruptions associated with crises events.

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