Cyborging HRM theory: from evolution to revolution – the challenges and trajectories of AI for the future role of HRM DOI
Edna Rabenu, Yehuda Baruch

Personnel Review, Год журнала: 2024, Номер unknown

Опубликована: Окт. 7, 2024

Purpose Human Resource Management (HRM) is a critical organizational function, which has continued to evolve. We aim explore how different HRM will be in the workplace of future and why, from both strategic practical perspectives. present discuss core practices, such as recruitment, selection training, well peripheral activities, monitoring health safety, diversity management, reflecting on they may transform future. Design/methodology/approach This conceptual thought piece, building Substitution, Augmentation, Modification Redefinition (SAMR) model, offer futuristic view era AI. Findings Discussing contemporary challenges Artificial Intelligence, we predict lead what term Cyborging HRM. Practical implications study can help HR managers practitioners prepared for AI-embedded systems For academics, it offers an innovative framework establish writing AI era. Originality/value pushing profession have undergo revolutionary rather than evolutionary transformation order remain necessary valuable function organizations. Our elaboration SAMR model suggested should worthwhile organizations, management wider society.

Язык: Английский

Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT DOI Creative Commons
Pawan Budhwar, Soumyadeb Chowdhury, Geoffrey Wood

и другие.

Human Resource Management Journal, Год журнала: 2023, Номер 33(3), С. 606 - 659

Опубликована: Июль 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.

Язык: Английский

Процитировано

363
AI-Augmented HRM: Literature review and a proposed multilevel framework for future research DOI Creative Commons
Verma Prikshat,

Mohammad Islam,

Parth Patel

и другие.

Technological Forecasting and Social Change, Год журнала: 2023, Номер 193, С. 122645 - 122645

Опубликована: Май 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.

Язык: Английский

Процитировано

58
Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda DOI Creative Commons

R. Deepa,

Srinivasan Sekar, Ashish Malik

и другие.

Technological Forecasting and Social Change, Год журнала: 2024, Номер 202, С. 123301 - 123301

Опубликована: Март 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.

Язык: Английский

Процитировано

27
Generative Artificial Intelligence in Business: Towards a Strategic Human Resource Management Framework DOI Creative Commons
Soumyadeb Chowdhury, Pawan Budhwar, Geoffrey Wood

и другие.

British Journal of Management, Год журнала: 2024, Номер 35(4), С. 1680 - 1691

Опубликована: Апрель 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.

Язык: Английский

Процитировано

21
Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace DOI Creative Commons
Ali Fenwick, Gábor Molnár,

Piper Frangos

и другие.

Frontiers in Artificial Intelligence, Год журнала: 2024, Номер 6

Опубликована: Янв. 15, 2024

The functions of human resource management (HRM) have changed radically in the past 20 years due to market and technological forces, becoming more cross-functional data-driven. In age AI, role HRM professionals organizations continues evolve. Artificial intelligence (AI) is transforming many practices throughout creating system process efficiencies, performing advanced data analysis, contributing value creation organization. A growing body evidence highlights benefits AI brings field HRM. Despite increased interest AI-HRM scholarship, focus on human-AI interaction at work AI-based technologies for limited fragmented. Moreover, lack considerations tech design deployment can hamper digital transformation efforts. This paper provides a contemporary forward-looking perspective strategic human-centric plays within as becomes integrated workplace. Spanning three distinct phases integration (technocratic, integrated, fully-embedded), it examines technical, human, ethical challenges each phase suggestions how overcome them using approach. Our importance evolving AI-driven organization roadmap bring humans machines closer together

Язык: Английский

Процитировано

18
Interactive effects of AI awareness and change-oriented leadership on employee-AI collaboration: The role of approach and avoidance motivation DOI
Zihan Yin, Haiyan Kong, Yehuda Baruch

и другие.

Tourism Management, Год журнала: 2024, Номер 105, С. 104966 - 104966

Опубликована: Май 20, 2024

Язык: Английский

Процитировано

16
Artificial intelligence for international business: Its use, challenges, and suggestions for future research and practice DOI Creative Commons
Jane Menzies, Bianka Sabert, Rohail Hassan

и другие.

Thunderbird International Business Review, Год журнала: 2024, Номер 66(2), С. 185 - 200

Опубликована: Фев. 9, 2024

Abstract The emergence of artificial intelligence (AI) has transformed global business, aiding operational efficiency and innovation. It utilizes machine learning big data analytics, driving predictive market trends strategic decision‐making. However, despite the rising discussion accessibility AI tools, understanding its impact on international business remains limited. This article explores AI's potential in strategies, practices, activities. To address this aim, we reviewed 37 articles existing literature to critically explore within context business. More specifically, explored how can be applied innovation approaches selection, entry modes, foreign exchange, human resource management, supply chains, managing across cultures, more topics. necessitated changes workplace configurations need for organizational employee adjustments response technology. As a result foregoing issues integration our analysis provided an exploratory around use, challenges, managerial implications, suggested areas requiring future studies.

Язык: Английский

Процитировано

15
Business Model Innovation through AI Adaptation: The Role of Strategic Human Resources Management DOI Creative Commons
Sanjit Kumar Roy, Bidit Lal Dey, David Brown

и другие.

British Journal of Management, Год журнала: 2025, Номер unknown

Опубликована: Янв. 21, 2025

Abstract While artificial intelligence (AI) requires business model innovation, it simultaneously poses persistent operational, regulatory and strategic challenges, highlighting the importance of researching AI adaptation to appropriate organizational value. is not monolithic, its nature consequent value appropriation processes may vary due external factors an organization's approach innovation resource management. Accordingly, a taxonomy link with can yield theoretical understanding practical implications why how organizations in leveraging human management shape led by adaptation. In this paper, we address issue applying adaptive structuration theory conducting interviews top personnel from 51 companies based India. Based on our findings, develop novel (exploitive, exploratory, emancipatory expedient), structured within 2 × matrix robust dynamic environment.

Язык: Английский

Процитировано

3
The Machine Learning-Based Task Automation Framework for Human Resource Management in MNC Companies DOI Creative Commons

Suchitra Deviprasad,

N. Madhumithaa,

I. Walter Vikas

и другие.

Опубликована: Дек. 18, 2023

Recently, machine learning-based task automation framework have been gaining attention in human resource management of Multi-National Companies (MNCs). Task helps MNCs to automate repetitive HR tasks, analyse data quickly and accurately, forecast workforce, recognize employees. are now beginning use ML algorithms combination with Artificial Intelligence (AI) streamline the processes. Most large-scale operations decentralized organization structures which put additional pressure on teams carry out intricate tedious manual To ease process, ML-based facilitates leverage power AI perform tasks a more effective efficient manner. The utilizes bots can simulate all processes such as recruitment, time attendance, tracking employee records, scheduling calendar, office administration tasks. predictive analytics identify trends, patterns, behaviour, anomalies, important insights from large volumes structured unstructured data.

Язык: Английский

Процитировано

22
From HAL to GenAI: Optimizing chatbot impacts with CARE DOI Creative Commons
Cai Feng, Elsamari Botha, Leyland Pitt

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 537 - 548

Опубликована: Апрель 17, 2024

This article explores the evolution and prospects of conversational chatbots, specifically latest generation referred to as Generative Artificial Intelligence (GenAI) chatbots. comprehensively examines GenAI chatbots' business applications impact across macro, meso, micro levels organizations. At Macro level, this how chatbots reshapes industry dynamics. The Meso perspective delves into organizational changes, while Micro lens focuses on enhancing individual productivity, learning, creativity. However, immense potential is accompanied by risks in four META areas – Matching, Ethics, Technology, Adaptability. In response these challenges, introduces a human-centric CARE framework Collaboration, Accountability, Responsiveness, Empowerment mitigate optimize impacts brought work provides practical guidelines navigate complex landscape implementation.

Язык: Английский

Процитировано

13