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

• Published date: 01 July 2023
• Author: 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 Rogelberg,Mark N. K. Saunders,Rosalie L. Tung,Arup Varma
• Date: 01 July 2023
• DOI: http://doi.org/10.1111/1748-8583.12524

606

Correspondence

Soumyadeb Chowdhury.

Email: s.chowdhury@tbs-education.fr

INVITED REVIEW

Human resource management in the age of

generative artificial intelligence: Perspectives and

research directions on ChatGPT

Pawan Budhwar12

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David Guest161718

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DOI: 10.1111/1748-8583.12524

Received: 5 June 2023 Revised: 8 June 2023 Accepted: 9 June 2023

AI, artificial intelligence; BERT, bidirectional encoder representations from transformers; EDI, equity diversity inclusion; ER, employee

relations; GPT, generative pre-trained transformer; HRM, human resource management; IHRM, international human resource management; IoT, internet of

things; IP, intellectual property; IT, information technology; KBV, knowledge based view; LLM, large language model; ML, machine learning; RBV, resource

based view; RLHF, reinforcement learning with human feedback; MOOCs, massive open online courses; SaaS, software-as-a-service; SHRM, strategic

human resource management.

The contributors and editors are listed in alphabetical order of their surnames. Each perspective is assigned to a section based on its relevance. The sections

are organised to make the flow of the narrative logical, easy to navigate, insightful and compelling.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits

use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or

adaptations are made.

© 2023 The Authors. Human Resource Management Journal published by John Wiley & Sons Ltd.



ChatGPT and its variants that use generative artificial

intelligence (AI) models have rapidly become a focal point

in academic and media discussions about their poten-

tial benefits and drawbacks across various sectors of the

economy, democracy, society, and environment. It remains

unclear whether these technologies result in job displace-

ment or creation, or if they merely shift human labour

by generating new, potentially trivial or practically irrel-

evant, information and decisions. According to the CEO

Hum Resour Manag J. 2023;33:606–659. wileyonlinelibrary.com/journal/hrmj

607

BUDHWARetal.

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 rela-

tionships, 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 appli-

cations, while heightening risks related to well-being, bias,

misinformation, context insensitivity, privacy issues, ethi-

cal 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 synthe-

sizes 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.



artificial intelligence, ChatGPT, CSR, ethics, generative AI, HRM,

human resource strategy, international human resource manage-

ment, productivity, sustainability



What is currently known?

• The rapid evolution of artificial intelligence models has swiftly

prompted much academic and media discourse regarding

their potential for disruption as well as their transformative

power impacting multiple facets of the economy, society, and

environment.

• Software tools like ChatGPT and other comparable ones

utilizing generative AI models can produce incredibly human-like

responses to queries, yet, they can also be profoundly erroneous,

raising significant ethical and moral issues, and their adoption by

HRM practitioners.

What this perspectives editorial adds?

• Provides a comprehensive summary of the advancements,

constraints, and commercial applications of generative AI.

• Offers 11 perspectives that advance scholarship in HRM and

present a collection of unexplored research opportunities for

HRM scholars.

608 BUDHWARetal.

This HRMJ perspectives editorial brings together a collection of viewpoints on how we can advance scholarship in

human resource management (HRM) considering the rapid developments in generative artificial intelligence (AI) and

their emerging implications for work processes in general and HRM in particular. In doing so, the primary purpose

is twofold: first, to provide an overview regarding the developments in the field, and two, to develop a portfolio of

research opportunities that will help HRM scholars to engage in impactful research advancing our understanding

about generative AI, by theorizing and providing empirical evidence, to push the existing scientific boundaries. To get

a comprehensive overview of the continuously evolving scene, we invited leading scholars to provide perspectives

into key themes core to HRM. The perspectives underscore the need for HR professionals to understand and adapt

to the changing AI landscape, particularly the transformative and disruptive potentials of generative AI on HRM plan-

ning, practices, processes, platforms, and productivity.



Pawan Budhwar 1, Soumyadeb Chowdhury 2, and Geoffrey Wood 3,4,5,6

Artificial Intelligence (AI) tools and digital platforms, or at least tools and platforms that claim “intelligent status”

have become an indispensable part for business organisations and society over the past decade. This stems from

AI algorithms' ability to automate business processes, extract knowledge from big data, provide predictions and

recommendations, and superior analytical and computational capabilities compared to human beings (von Krogh,

Roberson and Gruber, 2023). The various forms of AI such as robotic process automation (e.g., cobots in ware-

houses), computer vision techniques, speech recognition, machine and deep learning algorithms, and natural

language processing have created a plethora of opportunities and unique capabilities for organisations to redesign

business processes and functions, innovate business models and offerings in consumer space (like data-driven agile

and objective decision-making, project management and strategizing critical productivity indicators) (Kiron, 2022;

Schrage et al., 2023). At the same time, as with many recent technological advances, it is difficult to disentangle

hype from substance, and AI has proven more successful in some areas (e.g., generating superficially credible writ-

ten text) than others (e.g., robots with genuine dexterity). It remains uncertain if generative AI deskills or destroys

jobs, and/or creates new ones. It is paradoxical insofar as it takes work out of human hands and creates more work

for humans by generating new information and decisions to be made in areas that may be of major importance or

trivial.

In the past 5 years, human resource management (HRM) scholarship on AI has increased (Budhwar et al., 2022;

Chowdhury et al., 2023; Edwards et al., 2022; Malik, Budhwar, & Kazmi, 2022). For instance, recent studies have

emphasised the benefits of employing AI-based machine learning (ML) tools to promote diversity (Daugherty

The implications for practitioners

• Comprehending the possible strengths and weaknesses of

implementing immersive technologies like ChatGPT and its

variants in HRM strategy, practices, procedures, platforms, and

productivity will aid organisations' leaders in critically evaluating

its relevance, feasibility to implement, usefulness and potential

impact to achieve organisationally valued outcomes.

• The lack of regulations heightens the risks and ethical dilemmas

associated with the usage of generative AI models, which

presents significant threats for organisations, scholarly research,

and society at large.