Artificial intelligence (AI) in the world of work: bibliometric insights and mapping opportunities and challenges DOI

Ashish Malik,

Pamela Lirio, Pawan Budhwar

и другие.

Personnel Review, Год журнала: 2025, Номер unknown

Опубликована: Янв. 31, 2025

Purpose This editorial review presents a bibliometric account of the convergence fields artificial intelligence (AI) and human resource management (HRM) an overview related contributions in this special issue. It also explores expansive area where research on AI HRM intersects, domain experiencing rapid growth transformation, faster than we envisaged. Design/methodology/approach substantive employs range analytical tools to present state knowledge topic provides Special Issue. Findings A thorough examination scholarly publications spanning two decades illuminates evolutionary path themes, key contributors, seminal works emerging trends within interdisciplinary sphere. Leveraging co-word analysis, distill essential themes insights from extensive dataset 654 journal curated Web Science database. Our analysis underscores critical domains, highlighting nuanced interplay between AI. Originality/value By integrating findings papers Issue, highlight speculate field is heading scholars have crucial? Opportunities contribute going forward.

Язык: Английский

Artificial intelligence adoption in extended HR ecosystems: enablers and barriers. An abductive case research DOI Creative Commons

Antarpreet Singh,

Jatin Pandey

Frontiers in Psychology, Год журнала: 2024, Номер 14

Опубликована: Янв. 24, 2024

Artificial intelligence (AI) has disrupted modern workplaces like never before and induced digital workstyles. These technological advancements are generating significant interest among HR leaders to embrace AI in human resource management (HRM). Researchers practitioners keen investigate the adoption of HRM resultant human–machine collaboration. This study investigates specific factors that enable inhibit extended ecosystems adopts a qualitative case research design with an abductive approach. It studies three well-known Indian companies at different stages functions. key enablers such as optimistic collaborative employees, strong leadership, reliable data, specialized partners, well-rounded ethics. The also examines barriers adoption: inability have timely pulse check employees’ emotions, ineffective collaboration employees experts well external not embracing contributes theory by providing model for proposes additions unified acceptance use technology context ecosystems. best-in-class industry practices policy formulation reimagine workplaces, promote harmonious human–AI collaboration, make future-ready wake massive disruptions.

Язык: Английский

Процитировано

12
Employees' training experience in a metaverse environment? Feedback analysis using structural topic modeling DOI

Abubakr Saeed,

Ashiq Ali,

Saira Ashfaq

и другие.

Technological Forecasting and Social Change, Год журнала: 2024, Номер 208, С. 123636 - 123636

Опубликована: Авг. 15, 2024

Язык: Английский

Процитировано

12
Blinded by “algo economicus”: Reflecting on the assumptions of algorithmic management research to move forward DOI Creative Commons
Laura Lamers, Jeroen Meijerink, Giorgio Rettagliata

и другие.

Human Resource Management, Год журнала: 2024, Номер 63(3), С. 413 - 426

Опубликована: Янв. 23, 2024

Abstract This paper reflects on the paradigmatic assumptions and ideologies that have shaped algorithmic management research. We identify two sets of assumptions: one about “ontology algorithms” (which holds human resource [HRM] algorithms are non‐human entities with material agency) management” HRM afford understands as a form control for maximizing economic/shareholder value). explain how these core underpin existing research algorithms, causing blind spots hinder new ways understanding studying management. After identifying unpacking spots, we offer avenues to overcome allowing future based ideological assumption grounds will help move scholarship further in significant ways.

Язык: Английский

Процитировано

10
AI and HRM in Tourism and Hospitality in Egypt: Inevitability, Impact, and Future DOI

Bassam Samir Al‐Romeedy

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

9
The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges DOI Creative Commons
Justine Dima, Marie‐Hélène Gilbert, Julie Dextras-Gauthier

и другие.

Frontiers in Psychology, Год журнала: 2024, Номер 15

Опубликована: Июнь 3, 2024

This study analyzes the existing academic literature to identify effects of artificial intelligence (AI) on human resource (HR) activities, highlighting both opportunities and associated challenges, roles employees, line managers, HR professionals, collectively referred as triad.

Язык: Английский

Процитировано

8
When Healthcare Professionals Use AI: Exploring Work Well-Being Through Psychological Needs Satisfaction and Job Complexity DOI Creative Commons
Weiwei Huo,

Q. Li,

Bingqian Liang

и другие.

Behavioral Sciences, Год журнала: 2025, Номер 15(1), С. 88 - 88

Опубликована: Янв. 18, 2025

This study examines how the use of artificial intelligence (AI) by healthcare professionals affects their work well-being through satisfaction basic psychological needs, framed within Self-Determination Theory. Data from 280 across various departments in Chinese hospitals were collected, and hierarchical regression analyzed to assess relationship between AI, needs (autonomy, competence, relatedness), well-being. The results reveal that AI enhances indirectly increasing these needs. Additionally, job complexity serves as a boundary condition moderates Specifically, weakens autonomy while having no significant effect on relatedness. These findings suggest impact professionals’ is contingent complexity. highlights promoting at context adoption requires not only technological implementation but also ongoing adaptation meet evolving insights provide theoretical foundation practical guidance for integrating into support professionals.

Язык: Английский

Процитировано

1
A Bibliometric Analysis of Artificial Intelligence and Human Resource Management Studies DOI
Azizan Bin Morshidi, Nurhizam Safie Mohd Satar,

Azueryn Annatassia Dania Aqeela Azizan

и другие.

Advances in human resources management and organizational development book series, Год журнала: 2023, Номер unknown, С. 85 - 117

Опубликована: Дек. 29, 2023

The pervasiveness of artificial intelligence (AI) within contemporary organisations is an undeniable phenomenon. primary objective this chapter to undertake a meticulous bibliometric analysis the scholarly literature that investigates interconnected exploration utilisation and ramifications realm human resource management (HRM). researchers consulted valued scientific database Scopus, which proved be fount knowledge. Ninety-one documents were initially retrieved meticulously chosen for analysis. data underwent processing through esteemed Bibliometrix software sophisticated Biblioshiny application tool. results evince (HRM) constitutes emerging domain inquiry, characterised by continuous unwavering expansion promising trajectory future. Finally, discourse examined comparative themes emerged before after advent COVID-19 pandemic.

Язык: Английский

Процитировано

16
Navigating AI transitions: how coaching leadership buffers against job stress and protects employee physical health DOI Creative Commons
Jeeyoon Jeong, Byung‐Jik Kim, Julak Lee

и другие.

Frontiers in Public Health, Год журнала: 2024, Номер 12

Опубликована: Март 27, 2024

The dynamic interplay between Artificial Intelligence (AI) adoption in modern organizations and its implications for employee well-being presents a paramount area of academic exploration. Within the context rapid technological advancements, AI’s promise to revolutionize operational efficiency juxtaposes challenges relating job stress health. This study explores nuanced effects on physical health within organizational settings, investigating potential mediating role moderating influence coaching leadership. Drawing from conservation resource theory, research hypothesized that AI would negatively impact both directly indirectly through increased stress. Critically, our conceptual model underscores Further, introducing novel dimension this discourse, we postulate To empirically test hypotheses, gathered survey data 375 South Korean workers with three-wave time-lagged design. Our results demonstrated all hypotheses were supported. have significant strategies concerning implementation leadership development.

Язык: Английский

Процитировано

7
Applying generative AI ethically in HRD practice DOI
Lyle Yorks,

Michellana Y. Jester

Human Resource Development International, Год журнала: 2024, Номер 27(3), С. 410 - 427

Опубликована: Апрель 16, 2024

The purpose of this paper is to provide a framework for overseeing that applications artificial intelligence are ethically implemented and applied. With the expanding use Generative AI (GAI) such as ChatGPT, Bard, DALL-E, DeepMind, growing adoption these technologies in Human Resource Development (HRD), there pressing need address ethical implications technologies. challenges associated with GAI include bias, fairness, transparency, safety control, displacement job loss, privacy intrusion, humanity, agency. These concerns have significant HRD practices broader organisational ecosystem. However, lack comprehensive frameworks guidelines related present, ensuring responsible humane HRD. There push boundaries thinking about impact develop guiding practices, promoting privacy. This provides addressing challenges.

Язык: Английский

Процитировано

7
A systematic literature review on artificial intelligence in recruiting and selection: a matter of ethics DOI
Martina Mori, Sara Sassetti, Vincenzo Cavaliere

и другие.

Personnel Review, Год журнала: 2024, Номер unknown

Опубликована: Июль 17, 2024

Purpose Starting from the relevance of ethics to application artificial intelligence (AI) in context employee recruitment and selection (R&S), this article, we aim provide a comprehensive review literature light main ethical theories (utilitarian theories, justice, rights) identify future research agenda practical implications. Design/methodology/approach On basis best-quality most influential journals, conducted systematic 120 articles two databases (Web Science Scopus) descriptive results adopt framework for deductive classification topics. Findings Inspired by three identified thematic lines enquiry debate on AI R&S: (1) utilitarian view: efficient optimisation R&S through AI; (2) justice perceptions fairness related techniques; (3) rights respect legal human requirements when is applied. Originality/value This article provides detailed assessment adoption process standpoint traditional offers an integrative theoretical broader field HRM.

Язык: Английский

Процитировано

7