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

Human Resource Management Journal, Journal Year: 2023, Volume and Issue: 33(3), P. 606 - 659

Published: July 1, 2023

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

Language: Английский

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Employee experience –the missing link for engaging employees: Insights from an MNE's AI‐based HR ecosystem

Human Resource Management, Journal Year: 2022, Volume and Issue: 62(1), P. 97 - 115

Published: July 20, 2022

Abstract Analyzing multiple data sources from a global information technology (IT) consulting multinational enterprise (MNE), this research unpacks the configuration of digitalized HR ecosystem artificial intelligence(AI)‐assisted human resource management (HRM) applications and platforms. This study develops novel theoretical framework mapping nature purpose AI‐assisted for delivering exceptional employee experience (EX), an antecedent to engagement (EE). Employing lenses EX, EE, AI‐mediated social exchange, platforms, study's overarching aim article is establish how HRM fits into organization's and, second, it impacts EX EE. Our findings show that enhance thus, We also see increases in productivity function's effectiveness. Implications practice are discussed.

Language: Английский

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Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework

Human Resource Management Review, Journal Year: 2022, Volume and Issue: 33(1), P. 100940 - 100940

Published: Nov. 16, 2022

Language: Английский

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AI-Augmented HRM: Literature review and a proposed multilevel framework for future research

Technological Forecasting and Social Change, Journal Year: 2023, Volume and Issue: 193, P. 122645 - 122645

Published: May 24, 2023

The research using artificial intelligence (AI) applications in HRM functional areas has gained much traction and a steep surge over the last three years. extant literature observes that contemporary AI have augmented HR functionalities. AI-Augmented HRM(AI) assumed strategic importance for achieving domain-level outcomes organisational sustainable competitive advantage. Moreover, there is increasing evidence of reviews pertaining to use different management disciplines (i.e., marketing, supply chain, accounting, hospitality, education). There considerable gap existing studies regarding focused, systematic review on HRM(AI), specifically multilevel framework can offer scholars platform conduct potential future research. To address this gap, authors present (SLR) 56 articles published 35 peer-reviewed academic journals from October 1990 December 2021. purpose analyse context chronological distribution, geographic spread, sector-wise theories, methods used) theoretical content (key themes) identify gaps robust Based upon SLR, noticeable gaps, mainly stemming - unequal distribution previous terms smaller number sector/country-specific studies, absence sound base/frameworks, more routine functions(i.e. recruitment selection) significantly less empirical We also found minimal links organisational-level outcomes. overcome we propose offers researchers draw linkage among diverse variables starting contextual level eventually enhance operational financial performance.

Language: Английский

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Critical exploration of AI-driven HRM to build up organizational capabilities

Employee Relations, Journal Year: 2023, Volume and Issue: 45(5), P. 1057 - 1082

Published: May 4, 2023

Purpose Human resource management (HRM) processes are increasingly artificial intelligence (AI)-driven, and HRM supports the general digital transformation of companies' viable competitiveness. This paper points out possible positive negative effects on HRM, workplaces workers’ organizations along HR its potential for competitive advantage in regard to managerial decisions AI implementation regarding augmentation automation work. Design/methodology/approach A systematic literature review that includes 62 international journals across different disciplines contains top-tier academic German practitioner was conducted. The analysis applies resource-based view (RBV) as a lens through which explore AI-driven source organizational capabilities. Findings shows four ambiguities might support sustainable company development or prevent application: job design, transparency, performance data ambiguity. limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused general, recruiting analytics particular. Research limitations/implications ambiguities' context-specific capability building firms is indicated, avenues developed. Originality/value critically explores structures must addressed by strategically contribute an organization's advantage.

Language: Английский

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Systematic literature review of human–machine collaboration in organizations using bibliometric analysis

Management Decision, Journal Year: 2023, Volume and Issue: 61(10), P. 2920 - 2944

Published: Feb. 13, 2023

Purpose This study aims to systematically map the state of work on human–machine collaboration in organizations using bibliometric analysis. Design/methodology/approach The authors used a systematic literature review survey 111 articles published leading journals categorize theories and construct framework organizations. A analysis is applied statistically evaluate materials measure influence publications co-citation, coupling keyword analyses. Findings results inform that research organizational field targeted at four aspects: performance, innovation, human resource management information technology (IT). Originality/value first exploratory piece assess extent depth collaboration.

Language: Английский

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How does work autonomy in human-robot collaboration affect hotel employees’ work and health outcomes? Role of job insecurity and person-job fit

International Journal of Hospitality Management, Journal Year: 2023, Volume and Issue: 117, P. 103654 - 103654

Published: Dec. 5, 2023

Language: Английский

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Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 202, P. 123301 - 123301

Published: March 5, 2024

Research on the application of Artificial Intelligence (AI)-based technologies in HRM domain has attracted significant scholarly attention. Yet, few studies have consolidated key trends adopting AI for HRM, especially managerial competencies required AI-based and identifying research directions HR managers, including development an AI-focused competency framework managers. A systematic literature review (SLR) bibliometrics analysis were conducted to identify current direction managers HRM. Several themes capabilities identified, utilizing Dynamic Capabilities View (DCV). The SLR identified applications various tools techniques functions, recruitment selection was one with broadest use applications. Managerial cognitive capability, human capital, social capital DCV considered initial coding categories under which are adoption This study utilized SLR, Bibliometric, directed content as three distinct but interrelated sets methodologies extracting novel insights into It highlights associated that need mapping its adoption.

Language: Английский

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The impact of automation on maritime workforce management: A conceptual framework

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(5), P. 1467 - 1488

Published: May 4, 2024

This study presents a systematic literature review and content analysis focused on the impact of automation maritime workforce management. The main objective was to explore how integration technologies is reshaping skills requirements, employment patterns, operational dynamics within industry. Utilizing comprehensive search strategy across multiple academic databases employing stringent inclusion exclusion criteria, identified analyzed relevant peer-reviewed articles, conference papers, industry reports published in English. methodology involved detailed examination selected literature, categorizing findings according effects dynamics, skill socio-economic implications for professionals. Key highlight significant shift towards higher demand technical proficiency digital literacy among workforce, coupled with potential decrease traditional manual roles. also revealed dual automation, offering opportunities enhanced efficiency safety, while posing challenges related displacement need extensive re-skilling. Conclusively, underscores necessity strategic interventions by stakeholders, including targeted training programs policy frameworks, facilitate smooth transition an automated future. Future research directions emphasize importance longitudinal studies assess long-term impacts ensuring sustainable technological advancements safeguarding worker welfare growth. Keywords: Maritime Automation, Workforce Management, Skills Development, Technological Advancement

Language: Английский

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Generative Artificial Intelligence in Business: Towards a Strategic Human Resource Management Framework

British Journal of Management, Journal Year: 2024, Volume and Issue: 35(4), P. 1680 - 1691

Published: April 11, 2024

Abstract As businesses and society navigate the potentials of generative artificial intelligence (GAI), integration these technologies introduces unique challenges opportunities for human resources, requiring a re‐evaluation resource management (HRM) frameworks. The existing frameworks may often fall short capturing novel attributes, complexities impacts GAI on workforce dynamics organizational operations. This paper proposes strategic HRM framework, underpinned by theory institutional entrepreneurship sustainable organizations, integrating within practices to boost operational efficiency, foster innovation secure competitive advantage through responsible development. Central this framework is alignment with business objectives, seizing opportunities, assessment orchestration, re‐institutionalization, realignment embracing culture continuous learning adaptation. approach provides detailed roadmap organizations successfully GAI‐enhanced environment. Additionally, significantly contributes theoretical discourse bridging gap between adoption, proposed accounting GAI–human capital symbiosis, setting stage future research empirically test its applicability, explore implications understand broader economic societal consequences diverse multi‐disciplinary multi‐level methodologies.

Language: Английский

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