Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT

Pawan Budhwar, Soumyadeb Chowdhury, Geoffrey Wood, Herman Aguinis, Greg J. Bamber, Jose R. Beltran, Paul Boselie, Fang Lee Cooke, Stephanie Decker, Angelo DeNisi, Prasanta Kumar Dey, David Guest, Andrew J. Knoblich, Ashish Malik, Jaap Paauwe, Savvas Papagiannidis, Charmi Patel, Vijay Pereira, Shuang Ren, Steven RogelbergMark N.K. Saunders, Rosalie L. Tung, Arup Varma

Research output: Contribution to journalReview articlepeer-review

83 Citations (SciVal)

Abstract

ChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as “the printing press”, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the “AI arms race”, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well-being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.

Original languageEnglish
Pages (from-to)606-659
Number of pages54
JournalHuman Resource Management Journal
Volume33
Issue number3
Early online date10 Jul 2023
DOIs
Publication statusPublished - 31 Jul 2023

Bibliographical note

Funding Information:
Several people helpfully advised on earlier versions of parts of this perspectives editorial including Dale M Clarke and Dickson Lukose. Fang Lee Cooke would like to acknowledge the support of the Economic and Social Research Council (ESRC) through the Digital Futures at Work Research Center (grant no. ES/S012532/1). No funding has been specifically sought by authors for the topic covered in this article.

DATA AVAILABILITY STATEMENT
This is not an empirical article and does not use any form of primary data for analysis. Literature referred to in the article is listed in the bibliography.

Keywords

  • artificial intelligence
  • ChatGPT
  • CSR
  • ethics
  • generative AI
  • HRM
  • human resource strategy
  • international human resource management
  • productivity
  • sustainability

ASJC Scopus subject areas

  • Organizational Behavior and Human Resource Management

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