Title: Artificial Intelligence and Firm Performance: Does Machine Intelligence Shield Firms from Risks?

Abstract:

Artificial Intelligence (AI) has gained growing attention among different sectors of society, industries, and businesses in the past decade. The coronavirus pandemic (COVID-19) has accelerated and underscored the application of AI technology. The exponential growth of AI adoption has significant benefits for firm performance. However, prior studies mainly focused on theoretical aspects of the benefits of AI adoption on business processes. Empirical research on the impact of AI adoption on the performance of listed firms and security markets is underexplored and mainly focuses on the United States.

Therefore, this study empirically estimates and compares the impacts of the COVID-19 pandemic on the performance of AI-adopted and conventional listed firms globally using stock market indices. The single-group and multiple-group Interrupted Time-Series Analyses (ITSA) with panel data were used with four interventions: when the COVID-19 news spread and the pandemic entered the first, second, third, and fourth months (24/02/2020, 23/03/2020, 20/04/2020, and 18/05/2020, respectively).

The results show that the AI stock market outperformed the conventional stock market pre-COVID-19 period. The negative impacts of COVID-19 on the AI stock market were less severe than the conventional stock market in the first month of the pandemic. The performance of the AI stocks recovered quicker than the conventional stocks as the pandemic entered the third month. The results suggest that the AI stock market is more resilient than the non-AI stock market. Our study provides important evidence of the success of firms adopting AI in response to risks. Thus, the firms’ adoption of AI is a crucial driver for sustainable performance in challenging environments.

Artificial Intelligence (AI) has gained growing attention among different sectors of society, industries, and businesses in the past decade. The coronavirus pandemic (COVID-19) has accelerated and underscored the application of AI technology. The exponential growth of AI adoption has significant benefits for firm performance. However, prior studies mainly focused on theoretical aspects of the benefits of AI adoption on business processes. Empirical research on the impact of AI adoption on the performance of listed firms and security markets is underexplored and mainly focuses on the United States.

Therefore, this study empirically estimates and compares the impacts of the COVID-19 pandemic on the performance of AI-adopted and conventional listed firms globally using stock market indices. The single-group and multiple-group Interrupted Time-Series Analyses (ITSA) with panel data were used with four interventions: when the COVID-19 news spread and the pandemic entered the first, second, third, and fourth months (24/02/2020, 23/03/2020, 20/04/2020, and 18/05/2020, respectively).

The results show that the AI stock market outperformed the conventional stock market pre-COVID-19 period. The negative impacts of COVID-19 on the AI stock market were less severe than the conventional stock market in the first month of the pandemic. The performance of the AI stocks recovered quicker than the conventional stocks as the pandemic entered the third month. The results suggest that the AI stock market is more resilient than the non-AI stock market. Our study provides important evidence of the success of firms adopting AI in response to risks. Thus, the firms’ adoption of AI is a crucial driver for sustainable performance in challenging environments.

Biography:

Linh Tu Ho is a Lecturer in Finance, Faculty of Agribusiness and Commerce, Lincoln University, New Zealand. Her research focuses on investment, risk, and financial markets. With the applied quantitative approach, Linh has expanded her area to risk management, sustainable investment, finance technology, and green finance. She has won several research awards including the Sustainable Finance – INFINZ Prize and Semi-finalist of the InSPiR2eS Global PITCHING RESEARCH® Competition (IGPRC) 2022. Linh presented at several leading conferences, including the Accounting and Finance Association of Australia and New Zealand Conference (AFAANZ), International Congress on Modelling and Simulation (MODSIM) in Australia, and New Zealand Association of Economists Annual Conference (NZAE).