Artificial Intelligence in Human Resource Management: A Bibliometric Analysis Comparing Pre- and Post-COVID-19 Literature - Mahat, Dipak (PT FORMOSA CENDEKIA GLOBAL, 2024)
Existing research on AI applications in HRM has focused on specific functions with limited exploration of other areas. Changes in publication trends and focuses coinciding with COVID-19 require investigation. Study conducted a bibliometric analysis of 233 publications from 2015-2024 in the Scopus database, analyzing trends in sources, authorship, institutions, countries, keywords and themes. The results show an exponential surge in the annual number of publications since 2020, indicating that COVID-19 accelerated interest in AI-driven workforce innovations. Research efforts became more concentrated among prolific authors, core journals, and leading universities. Study reveals how the pandemic triggered substantive changes, transforming AI-HRM research into a more globally engaged and focused field. This is the first comprehensive bibliometric study to analyze how COVID-19 transformed AI-HRM research landscape in terms of quantitative trends, participants and investigated topics.